Age differences and profiles in pro-environmental behavior and eco-emotions

Abstract

Previous research suggests that age-related differences in pro-environmental behavior (PEB) and the emotional reactions to climate change could originate from generational as well as aging effects and can be influenced by the opportunities and constraints of life circumstances and resources. The current research aimed to better understand age differences through examining the eco-emotions and PEBs of different age groups, and identifying latent groups differing on these variables. In Sample 1, adults from the general population (n = 4,685) filled out questionnaires assessing eco-anxiety, eco-guilt, and ecological grief and answered 12 questions about their PEBs. In Sample 2 (A), the same PEB questions were answered by high school students (n = 112) and in Sample 2 (P) by one of their parents (n = 112). There were no age differences in the overall PEB score, but we found significant, nonlinear differences between age groups in almost all individual PEBs. Eco-friendly clothing and using greener transport were more common in the younger age groups, while older age groups had higher scores in conservation, recycling, reduced meat consumption, and boycotting. Students were less likely to recycle, use reusable bags, eat less meat and save water than their parents, but more likely to use greener transportation. Five latent groups emerged on the eco-emotions and PEB measures. Young adults had a higher probability of belonging to the medium/higher anxiety groups than the older generations, except for those in their 70s. Groups with higher emotional concern showed higher behavioral involvement. Since most participants showed a moderate level of worry, this emotional reaction appears a normative response to the climate crisis and also a possible starting point for promoting PEBs. The findings also suggest that each generation has its preferences in terms of PEBs, and it is worthwhile to address each of the different PEBs separately.

Keywords

Pro-environmental behavior eco-anxiety climate change anxiety eco-guilt ecological grief generations latent profile analysis

Introduction

Older generations have been confronted with the threats of both pollution (Carson et al., 1962) and climate change (Hansen, 2018) for decades, but effective action has yet to be taken. Recently, climate change has gained considerable media coverage (Hase et al., 2021), to which younger generations have been strongly exposed. However, there are inconsistent results on whether the different generations react differently to the ecological crisis on an emotional and behavioral level.

Climate Change–Related Emotions and Behavior

There is a growing literature on climate change–related emotions (Ogunbode et al., 2023; Pihkala, 2022), especially climate change anxiety (Ágoston, Csaba, et al., 2022; Ágoston, Urbán, et al., 2022; Clayton, 2020; Pihkala, 2020), which is a nonspecific worry or fear of environmental doom (Pihkala, 2020), ecological grief, which can be defined as a special type of grief felt upon anticipated or experienced ecological loss due to chronic or acute environmental change (Cunsolo & Ellis, 2018), and eco-guilt, which people experience when they feel that they violate environmental norms through their behavior or they think that they do not meet personal or societal environmental standards (Mallett, 2012). Pro-environmental behavior (PEB) is an umbrella term for the various individual actions taken to reduce negative human impacts on the natural environment (Mónus, 2021). It is possibly due to the complex nature of the concept that a wide variety of measurement tools have been developed to assess PEB (see Lange & Dewitte, 2019; Mónus, 2021), which have been shown to be valid estimates of realized PEB (Gaborieau & Pronello, 2021; Kaiser, 1998; Kormos & Gifford, 2014), although Rasch-type measurement tools tend to be more conservative as compared with simple composite measures which tend to overestimate objective (i.e., actual) PEB (Mónus, 2021).

It is worth noting that different PEBs have varying impacts on emissions: For example, line-drying clothes has minimal impact on emissions, thermostat setback (i.e., reducing how often the heating or cooling system operates) has slightly more impact, switching to a fuel-efficient car is even more effective while eating fewer animal products has the highest impact (Lacroix, 2018). However, the objective impact of an action is not necessarily in line with its perceived difficulty, and people might choose token behaviors—which are easy for the individual, but have low environmental impact—to reduce their guilt (Gifford, 2011). Detailed examination of the reported frequency of various PEBs is important, because it can shed light on their perceived difficulty (Kaiser, 1998; Mónus, 2021).

Age-Related Differences in Environmental Awareness, Attitudes, Emotions, and PEB

It is easy to find simple and contradictory statements on the links between generations and environmental awareness like “older people are more environmentally friendly” (Jordan, 2018, p. 106; Liobikienė & Juknys, 2016, p. 7; Wang et al., 2021), or in contrast, “younger people are more environmentally oriented” (Wikle, 1995, p. 42) and “younger people are more environmentally conscious” (Tsakiridou et al., 2009, p. 203). But recent studies examining the relationship between age and environmental consciousness have found inconsistent results (e. g., Domingues & Gonçalves, 2020; Gray et al., 2019; Sheoran & Kumar, 2022).

Many studies highlight a higher level of environmental awareness among young people. Younger people are slightly more positive about environmentally conscious behavior than older people in terms of intentions and attitudes (Wiernik et al., 2013) and younger age has been consistently found to be associated with increased climate/eco-anxiety or worry (Ágoston, Urbán, et al., 2022; American Psychological Association, 2018; Berry et al., 2018; Clayton & Karazsia, 2020; Hawcroft & Milfont, 2010; Heeren et al., 2022; Kácha et al., 2022; Searle & Gow, 2010). A recent systematic review strongly corroborates these observations (Boluda-Verdu et al., 2022) and a recent scoping review on eco-anxiety in children suggested that children’s and young people’s eco-anxiety could lead to various mental health outcomes like depression, sadness, anger, and fear (Léger-Goodes et al., 2022). A previous study showed that eco-guilt was also negatively correlated with age, but ecological grief was not associated with age (Ágoston, Urbán, et al., 2022). However, some of these papers are either theoretical (American Psychological Association, 2018; Berry et al., 2018) or address age as a linear construct (Ágoston, Urbán, et al., 2022; Heeren et al., 2022; Kácha et al., 2022).

When we focus on actual behavior instead of awareness and emotions, most research indicates that older people perform better: They are more likely to engage in conservation behaviors that are linked to the avoidance of environmental harm and the active protection of ecosystems, and conserve materials and natural resources ecosystems (e.g., reduce consumption, avoid waste, reuse, recycle), and are more likely to engage in outdoor activities (Wiernik et al., 2013). A recent international study examining participants from 31 countries found that older people engage in more PEB (Wang et al., 2021). National studies found that older people use less electric power (Moser & Kleinhückelkotten, 2018) and are more pro-environmental in recycling, purchases, and car use (López-Mosquera et al., 2015). However, Wiernik and colleagues (2013) also concluded that older people engage less often in “active” behaviors (e.g., joining environmental groups), and an early meta-analysis also found that younger individuals were slightly more likely to report engaging in PEBs than older people (Hines et al., 1987).

Only a few studies have compared PEBs of different age groups (instead of treating age as a continuous variable), and they concluded that there is no linear association between age and PEBs. For example, Patel et al. (2017) found a higher level of PEBs among middle-aged respondents (36–50 years) than among younger and older respondents in India. Another study found that hospitality employees in Generation Y (below 33 years) were more likely to embrace environmental initiatives than those in Generation X (between 33 and 53 years) (Kim et al., 2016). Generation Z (those below 25 years), however, seemed to be less engaged in PEB than people above 25 years according to a study in Poland (Parzonko et al., 2021).

Overall, then, current research suggests that younger people are more likely to express concern about sustainability but engage in less PEB, perhaps because they lack the necessary means or are not in a position to translate this concern into action. While older people are less concerned about the environment, they can still adopt environmentally friendly behaviors, perhaps due to thrifty habits. As noted by Torgler and Garcia-Valiñas (2007), the observed intergenerational differences may result from different sources: aging effects such as personal development and biological maturation of individuals, age-dependent changes in possibilities, expectations, motivations and personality traits, as well as changes in goals and perceptions concerning people’s rest of life (Carstensen et al., 1999; McCrae et al., 1999), and/or generational effects resulting from socialization in a particular era with specific experiences. This complexity of effects may contribute to inconsistent results regarding age-dependent PEBs and eco-emotions.

Most previous research has used broad age categories (e.g., “younger” and “older” people). However, when more detailed age disaggregation is applied in research on other constructs like executive control and self-esteem, nonlinear associations with age are often found (e.g., Cepeda et al., 2001; Robins & Trzesniewski, 2005). Such findings emphasize the value of using a more nuanced subcategorization of the stages of adulthood, such as young adulthood (20–29 years), young-middle adulthood (30–39 years), middle adulthood (40–49 years), middle-older adulthood (50–59 years), old adulthood (60–69 years), and older adulthood (70 years and over) (Cepeda et al., 2001).

The Interaction Between Different Generations

A very important, but less researched, issue is how generations affect each other. In a Danish study, there was a relationship between children’s and their parents’ environmental values, attitudes, and behaviors, but the strength of the relationship varied across behaviors: It was strong for buying environmentally friendly products, medium for sorting waste, and lower for saving electricity. Parents seemed to exhibit stronger PEB than their children (Grønhøj & Thøgersen, 2009). Another study in China found that parents’ PEBs were associated with their children’s PEBs except for energy conservation (Jia & Yu, 2021). The relationship may be best explained by the children’s awareness of the parental behavior: The intergenerational relationship was stronger if the behavior was more visible and unambiguous (Grønhøj & Thøgersen, 2012). Subjective norms (children’s beliefs about parents’ expectations for their behavior) also play an important role, although they seem to play a more important role in collectivistic cultures, such as Japan, than they do in individualistic cultures, such as Germany (Ando et al., 2014).

Latent Profile Analysis: A Person-Centered Approach to Identify Distinct Patterns of Eco-Emotions and PEB

Latent profile analysis (LPA) is a person-centered statistical approach which focuses on identifying latent subgroups within a population based on a certain set of variables (Howard & Hoffman, 2018). Using LPA can have several merits when exploring the relationship of different environment-related variables (e.g., emotions, behavior). In the case of eco-emotions (i.e., eco-anxiety, eco-guilt, and ecological grief), several studies found a positive relationship with PEB (Ágoston, Urbán, et al., 2022; Clayton & Karazsia, 2020; Mallett, 2012; Verplanken & Roy, 2013), whereas other studies emphasize that climate anxiety has a negative effect on general self-efficacy and that individuals whose self-efficacy is impaired due to climate change anxiety may not be able to engage in PEBs (Innocenti et al., 2023). LPA can help us to better understand individual patterns in the relationship between eco-emotions and behaviors. There are several examples of applying LPA to climate change–related variables. Sciberras and Fernando (2022) examined latent groups among Australian adolescents’ patterns of change in worry over an 8-year period and identified six groups: persistent worry, moderate worry, increasing worry, persistent low worry, slightly decreasing worry, and steeply decreasing worry. Jürkenbeck et al. (2021) identified three latent groups among young German citizens regarding climate change awareness, namely, a “highly aware,” a “denying,” and an “in-between” group, and found that participants in the “highly aware” group had a higher probability of following a climate-friendly diet than the other two groups. Rhead et al. (2018) identified four latent groups regarding environmental attitudes in a representative U.K. sample, namely, “pro-environment,” “neutral majority,” “disengaged,” and “paradoxical,” and found that membership in the “neutral majority” and “pro-environment” groups was positively associated with the majority of behavioral measures. A large-scale study in 23 countries (Kácha et al., 2022) with a comprehensive set of variables (e.g., climate change beliefs, concerns, pro-environmental personal norms, efficacy beliefs) identified four latent groups regarding climate change attitudes and beliefs, namely, “engaged,” “pessimistic,” “indifferent,” and “doubtful,” and found the highest PEB in the “engaged” group. Although these studies found that higher emotional engagement or concerns tend to be associated with higher behavioral engagement, other studies suggest that above a certain level, the level of distress can become maladaptive and, for example, have a negative influence on behavior (Heeren et al., 2022).

Based on the results of previous research, our study had four aims: (1) to examine the frequency of different PEBs across age groups segmented by decades, and thereby detect more subtle age differences in PEBs; (2) to examine the association in frequency of certain behaviors by parents and children living in the same household, which could shed light on generational differences and socialization effects; (3) to explore latent profiles of eco-emotions (anxiety, guilt, grief) and behavior, which could identify subgroups such as those in which high anxiety is paralyzing and hinders behavior, or groups with low anxiety but high behavioral involvement; and (4) to compare latent profiles across age groups.

Methods

Sample and Procedure

Data from two samples were used for the analyses. In Sample 1, adults (>18 years) from the general population participated in an anonymous online survey, which was advertised on a popular news website in Hungary between January and March 2021. Participants could continue with the questionnaire after they read and agreed to the informed consent. After excluding respondents who had missing data for key variables (eco-emotions, PEB), data from 4,685 participants were retained. We did not use any incentives for the recruitment of participants.

In Sample 2, student–parent dyads were recruited from 11 schools in Hungary (eight from Budapest and three from the countryside). Four schools in Budapest (one regular high school, one alternative high school, and two vocational high schools) were selected from the list of the Education Office using a random number generator. A financial incentive was offered to schools recruited through stratified sampling (1800 HUF [approx. US$6] for each fully completed questionnaire of a parent–student dyad, and 900 HUF [approx. US$3] for each fully completed student questionnaire without the parent’s questionnaire). To achieve a larger sample size, especially for the parent–student dyads, seven additional schools were contacted by word of mouth and invited without an incentive (two regular and two alternative high schools from Budapest, two regular high schools, and one alternative high school from the countryside). In January 2021, we contacted the heads of the selected secondary schools and, through them, the class teachers, who sent the link to the questionnaire to the students. Parents of students below18 years received a passive consent form before the data collection so that they could declare if they did not agree to their child completing the questionnaire. In the same letter, we asked them to complete a questionnaire measuring PEB. No parents refused the participation of their children. At the beginning of the online questionnaire, students and their parents were assured of anonymity and informed about the details and purpose of the survey. We use the data of students (n = 112) and one of their parents (n = 112); in the “Results” section below, “Sample 2 (A)” represents the adolescent sample and “Sample 2 (P)” represents the parent sample.

The studies were approved by the Research Ethics Committee of Eötvös Loránd University, Faculty of Education and Psychology (number of the ethical approval: 2020/481).

Measures

Demographic Questions

All participants were asked to provide their gender, age, and place of residence. All adults were asked about their educational attainment, while participants in Sample 1 were also asked to rate their subjective economic status (SES) (1 = is among the wealthiest, 7 = is among the poorest).

Pro-Environmental Behavior

All participants answered the Pro-Environmental Behavior Questionnaire (PEBQ) (Ágoston, Urbán, et al., 2022), which consists of 12 questions related to different PEBs and which was partly based on previous PEB scales (Brick & Lewis, 2014; Mónus, 2021; Urien & Kilbourne, 2010). Nine of the items (1. sorting waste into recycling bins; 2. composting or reusing household food garbage; 3. using reusable bags; 4. eating [less] meat; 5. eating (less) dairy products or eggs; 6. walking, cycling, or taking public transportation instead of using a car; 7. saving energy; 8. conserving water; and 9. using secondhand clothes) were rated on a 5-point scale. We used the following response options for Questions 1–3 and 6–8: 1 = never/almost never, 2 = rarely, 3 = moderately often, 4 = often, 5 = almost always/always. For the food-related questions (Questions 4–5), the participants could choose from the following options: 1 = never/almost never, 2 = rarely, 3 = at least weekly, 4 = daily, 5 = at each meal (the responses were reversed for the analyses). In the context of clothing (Question 9), we used the following options: 1 = new clothes only, 2 = most of the clothes are new, some used, 3 = half new, half used, 4 = most of the clothes are used, some new, 5 = secondhand clothes only. Three questions were dichotomous (being a member of an environmental organization; participating in an environmental protest; boycotting products made by environmental offenders).

Individual PEB items were analyzed separately in age group comparisons, while we calculated a single index of general PEB for the LPA. It was calculated based on each of the 12 PEBQ questions considering the principles laid down by Kaiser (1998) to deal with some relevant issues of PEB measurement (such as multidimensionality, which means that the items do not necessarily belong to one factor, and differences in behavior difficulties, that is, frequency of endorsement of the behavior). To calculate a general PEB index, Likert-type items were converted to dichotomous variables (4 and 5 points on Likert-type scales were converted to Yes/pro-environmental answers because these options indicate pro-environmental habits; 1, 2, and 3 points to No/non-pro-environmental answers). Subsequently, we assigned a weight for each of the 12 items: their inverse frequency in the whole sample, which represents the behavioral difficulty of the given activity.¹ A given pro-environmental activity was taken to be more difficult when only a small proportion of the sampled population reported frequently undertaking it. In the final step, for each respondent, we summarized the weights (behavioral difficulties) of those items in which participants were involved (see Rasch-type measures in Kaiser et al., 2018; Mónus, 2021). This index, which can range from 0 to 1 (larger numbers representing respondents engaging more often in PEBs), considers the behavioral difficulty of the items and provides a measure of a person’s general PEB (see Mónus, 2021).

Eco-Emotions

Participants in Sample 1 filled out the initial item pool that provided the basis for the 22-item Eco-Anxiety Questionnaire (EAQ-22), the 11-item Eco-Guilt Questionnaire (EGuiQ-11), and the 6-item Ecological Grief Questionnaire (EGriQ-6). The development and psychometric analysis of these questionnaires, which were conducted in the same sample, were published elsewhere (Ágoston, Urbán, et al., 2022). The EGuiQ-11 is a unifactorial, 11-item questionnaire, which measures the guilt people feel because of their polluting behavior (e.g., “The more I know about the human causes of climate change, the more things I feel guilty about.”). A higher score on the EGuiQ-11 indicates higher eco-guilt. The questionnaire had good internal consistency in the current study (Cronbach’s α = .89). The EGriQ-6 is a unifactorial, 6-item questionnaire, which measures the sense of loss and grief people feel related to ecological losses, such as the extinction of species or destruction of natural landscapes (e.g., “It makes me sad that I don’t see many of the plants and animals I used to see often.”). A higher score on the EGriQ-6 indicates higher ecological grief. The questionnaire had acceptable internal consistency in the current study (Cronbach’s α = .77).

The EAQ-22 is a two-factor questionnaire, which measures two aspects of eco-anxiety. The habitual ecological worry scale reflects the emotional reactions (e.g., fear, concern for themselves and others, anger toward polluters, frustration) related to the ecological crisis (sample item: “I feel sorry for those whose health is already negatively affected by climate change.”). The negative consequences of eco-anxiety scale focuses on consequences like poorer sleep, muscle tension, concentration problems, conflicts with family/friends, and loss of function at work/study (sample item: “My loved ones become irritated because I talk about my climate change concerns too often.”). A higher score on each scale indicates higher levels of habitual ecological worry and more negative consequences of anxiety, respectively. The internal consistency of the habitual ecological worry scale was excellent (Cronbach’s α = .91), while the internal consistency of the negative consequences of anxiety scale was good in the current study (Cronbach’s α = .86). The items of the three questionnaires were rated on a 4-point scale.

Statistical Analysis

We formed seven age groups for the comparisons: below 20 years (n = 145), 20–29 years (n = 717), 30–39 years (n = 1,210), 40–49 years (n = 1,438), 50–59 years (n = 773), 60–69 years (n = 457), and 70 years and above (n = 169). We used chi-square tests with Bonferroni-adjusted z-tests for pairwise comparisons and Kruskal–Wallis tests with Dwass-Steel-Critchlow-Fligner pairwise comparisons to compare age groups regarding the different PEB items. We compared the students’ and parents’ behavior with Wilcoxon tests—with rank-biserial correlation as an effect size indicator, which marks the difference between the proportions of negative and positive ranks over the total sum of ranks—and NcNemar tests.

We also conducted LPA on Sample 1, in which we included the z-scores for eco-guilt, eco-grief, and the two scales of eco-anxiety as well as the general PEB variable. To identify the best solution, we examined the Akaike information criteria (AIC), the Bayesian information criteria (BIC), the sample size–adjusted Bayesian information criteria (SABIC), and the Lo–Mendell–Rubin likelihood ratio test (LMR; also known as Vuong–Lo–Mendell–Rubin test), which are the most commonly used indices (Tein et al., 2013). In the case of AIC, BIC, and SABIC, the lower value indicates a better model (Bauer, 2022), while in the case of LMR, the p value indicates whether there is a significant improvement between the examined model and the model with one fewer class (a statistically significant result of the LMR supports the k-class model over k – 1 classes) (Tein et al., 2013; Urbán et al., 2011). Finally, we examined the entropy, which is ideally close to 1 (Bauer, 2022), and the interpretability of the profiles. The possible association between age groups and latent profiles was examined using a chi-square test.

We used the MPlus 6.0 statistical program (Muthén & Muthén, 1998–2011) for the LPA analyses and the Jamovi 2.3 (The Jamovi Project, 2019) and SPSS 25 (IBM Corp., 2011) for the other analyses.

Results

The demographic characteristics of the whole sample and the subsamples are presented in Table 1. Male participants were overrepresented in the general adult sample and the student sample and female participants were overrepresented in the parent sample. More than half of the participants lived in the capital city. The distribution (skewness and kurtosis) of the scales and the Pearson correlations between the scales are presented in Supplementary Table 1.

Table 1.

Demographic Characteristics of the Subsamples and the Total Sample.

Characteristics	Sample 1	Sample 2—students	Sample 2—parents	Total sample
Characteristics	(n = 4,685)	(n = 112)	(n = 112)	(N = 4,909)
Gender, n (%)
Female	1,969 (42.0)	42 (37.5)	89 (79.5)	2,100 (42.8)
Male	2,677 (57.1)	70 (62.5)	22 (19.6)	2,769 (56.4)
Other/do not want to answer	39 (0.8)	0 (0.0)	1 (0.9)	40 (0.8)
Age (years), M (SD)	43.3 (13.2)	17.0 (1.0)	47.0 (4.5)	42.8 (13.5)
Place of residence, n (%)
Budapest	2,380 (50.8)	73 (65.2)	67 (59.8)	2,520 (51.3)
Another city	1,758 (37.5)	29 (25.9)	33 (29.5)	1,820 (37.1)
Village	468 (10.0)	10 (8.9)	11 (9.8)	489 (10.0)
Missing	79 (1.7)	0 (0.0)	1 (0.9)	80 (1.6)
Educational attainment, n (%)
Elementary school or less/vocational school	75 (1.6)	—	10 (8.9)	85 (1.7)
High school/higher vocational education	1,058 (22.6)	—	54 (48.2)	1,112 (22.7)
College, university or higher	3,532 (75.4)	—	47 (42.0)	3,579 (72.9)
Missing	20 (0.4)	—	1 (0.9)	133 (2.7)
Subjective SES, M (SD)	3.2 (1.0)	—	—	3.2 (1.0)

SES = subjective socioeconomic status (ranges from 1 to 7; 1 means among the wealthiest).

Generational Differences in PEB

The frequency of each PEB varied considerably. The frequency of each behavior calculated from the dichotomized values is presented in Table 2.

Table 2.

The Frequency of Each Pro-Environmental Behavior.

Behavior	% of the participants practice it (always or at least often)
Membership in an environmental organization	6^a
Eating less dairy/egg	10^b
Second-hand clothes	19^b
Protesting	20^a
Eating less meat	21^b
Saving energy	37^b
Composting	42^b
Saving water	52^b
Boycotting	52^a
Greener transportation	61^b
Using reusable bags	80^b
Recycling	92^b
	N = 4,685

Yes.

Always or at least often.

General PEB and age were not correlated (r = –.009, p = .546). There were no differences between the age groups regarding membership in an environmental organization, participation in an environmental protest, and dairy/egg consumption, which were all low-frequency activities (for details, see Table 3). However, there were significant age differences in boycotting products made by environmental offenders: People in their 50s and 60s were more likely to report boycotting compared with people in their 20s (small effect size). There were also significant age differences in greener transportation (medium effect size), using reusable bags, eating less meat, saving water (small to medium effect size), recycling, composting, saving energy, and using secondhand clothes (very small effect size) (Table 3).²

Table 3.

Generational Differences in Pro-Environmental Behavior.

	Recycling^a	Compost-ing^a	Using reusable bags^a	Eating meat^b	Eating dairy/egg^b	Greener transport^a	Saving energy^a	Saving water^a	Second-hand clothes^c	Membership in an environmental organization	Protesting	Boycotting
	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	% yes within age group	% yes within age group	% yes within age group
Below 20 (n = 145)	4.49 (1.00)	2.99 (1.55)	3.82 (1.27)	2.14 (1.11)	2.20 (0.92)	3.89 (1.03)	2.77 (1.32)	3.26 (1.14)	2.08 (1.06)	4.8	15.2	47.6
20-29 (n = 717)	4.57 (0.92)	2.75 (1.50)	4.37 (0.98)	2.88 (1.26)	2.43 (1.09)	4.29 (1.05)	3.05 (1.22)	3.32 (1.10)	2.43 (1.16)	4.2	22.6	46.3
30-39 (n = 1,210)	4.64 (0.89)	2.68 (1.60)	4.32 (1.03)	2.70 (1.12)	2.33 (0.95)	3.92 (1.19)	2.97 (1.31)	3.30 (1.12)	2.17 (1.13)	6.0	18.6	51.0
40-49 (n = 1,438)	4.71 (0.80)	2.98 (1.64)	4.28 (1.08)	2.77 (1.03)	2.31 (0.88)	3.49 (1.32)	2.94 (1.27)	3.54 (1.07)	2.17 (1.14)	7.1	18.0	51.4
50-59 (n = 773)	4.68 (0.83)	3.06 (1.65)	4.16 (1.10)	2.77 (1.01)	2.29 (0.86)	3.29 (1.34)	2.95 (1.24)	3.62 (1.02)	2.10 (1.15)	7.1	21.0	54.7
60-69 (n = 457)	4.62 (0.89)	3.09 (1.65)	4.04 (1.14)	2.71 (0.86)	2.25 (0.70)	3.42 (1.26)	3.22 (1.24)	3.72 (1.00)	2.19 (1.14)	6.6	19.7	56.9
70 and above (n = 169)	4.65 (0.78)	3.17 (1.65)	3.89 (1.16)	2.79 (0.78)	2.30 (0.70)	3.51 (1.15)	3.31 (1.20)	3.66 (0.93)	2.39 (1.25)	3.6	20.7	56.8
Kruskal–Wallis/χ² test	32.59**	47.10**	91.23**	67.65**	6.25	349.22**	34.91**	89.70**	45.36**	10.9	10.0	19.2*
ε²/Cramer’s V	0.007	0.010	0.019	0.014	0.001	0.071	0.007	0.018	0.009	0.047	0.045	0.063

df for the Kruskal–Wallis/χ² tests = 6.

The item was scored from 1 to 5, where 1 = never/almost never, 2 = rarely, 3 = moderately often, 4 = often, 5 = almost always/always.

The item was scored from 1 to 5, where 1 = at each meal, 2 = daily, 3 = at least weekly, 4 = rarely, 5 = never/almost never.

The item was scored from 1 to 5, where 1 = new clothes only, 2 = most of the clothes are new, some used, 3 = half new, half used, 4 = most of the clothes are used, some new, 5 = secondhand clothes only.

p < .01. **p < .001.

As the pairwise comparisons (Table 4, Supplementary Figures 1–8) indicate, there were only minor generational differences in recycling: People in their 40s were more likely to report putting their waste in the recycling bin at home compared with those in their 20s and teenagers, while those in their 50s claimed that they were more likely to recycle than those in their 20s. Those in their 20s and 30s indicated that they were less likely to compost than the age groups over 40. Results regarding reusable bags were nonlinear: Teenagers were less likely to report using a reusable bag than other age groups up to the age of 60, while those in their 20s, 30s, and 40s were more likely to report doing so than those over 50. Teenagers stated that they ate meat more frequently than the other age groups. Teenagers and those in their 30s were more likely to report using eco-friendly transportation than those over 40, while those in their 20s were more eco-friendly in this regard than all the other age groups. People in their 60s and 70s reported that they were more likely to save electricity than the other age groups (except for those in their 20s), and people over 40 were more likely to report saving water than people in their 20s and 30s. Teenagers also reported saving less water than people in their 50s and 60s. Those in their 20s claimed that they were more likely to wear secondhand clothes than the rest of the age groups, except for those in their 70s.

Table 4.

Pairwise Comparisons of the Age Groups Regarding Pro-Environmental Behavior.

Group 1	Group 2	W (Dwass-Steel-Critchlow-Fligner pairwise comparison)
Group 1	Group 2	Recycling	Composting	Using reusable bags	Eating less meat	Eating less dairy/egg	Greener transportation	Saving energy	Saving water	Secondhand clothes
Below 20	20–29	1.12	−2.44	7.71***	9.43***	2.81	7.56***	3.59	0.67	4.76*
Below 20	30–39	3.45	−3.30	7.26***	8.53***	2.09	1.44	2.54	0.45	1.06
Below 20	40–49	5.03**	−0.12	6.86***	10.41***	2.10	−4.41*	2.27	3.83	0.97
Below 20	50–59	3.79	0.58	4.45*	10.20***	1.76	−6.85***	2.40	4.79*	−0.20
Below 20	60–69	2.31	0.81	2.51	9.97***	1.80	−5.42**	5.28**	6.01***	1.13
Below 20	70 and above	1.63	1.32	0.26	9.66***	2.28	−4.19*	5.23**	4.08	2.83
20–29	30–39	4.11	−1.79	−1.36	−4.08	−1.78	−10.41***	−1.80	−0.47	−7.01***
20–29	40–49	6.88***	4.36*	−2.11	−1.80	−2.05	−19.70***	−2.74	6.03***	−7.39***
20–29	50–59	4.41*	5.01**	−5.70**	−1.36	−2.22	−21.47***	−2.21	7.21***	−8.35***
20–29	60–69	1.95	4.78*	−7.85***	−1.73	−1.95	−17.73***	3.39	8.56***	−5.23**
20–29	70 and above	0.94	4.20*	−8.31***	0.32	−0.37	−12.55***	3.38	4.75*	−0.96
30–39	40–49	2.90	6.66***	−0.84	3.37	−0.18	−11.73***	−0.86	7.56***	−0.20
30–39	50–59	0.75	6.75***	−5.05**	3.24	−0.61	−14.74***	−0.43	8.51***	−2.31
30–39	60–69	−1.34	6.09***	−7.42***	2.39	−0.43	−10.67***	4.95**	9.62***	0.27
30–39	70 and above	−1.44	4.86*	−7.86***	3.47	0.90	−6.64***	4.40*	5.18**	2.79
40–49	50–59	−1.79	1.23	−4.42*	0.45	−0.47	−4.91**	0.33	2.13	−2.21
40–49	60–69	−3.57	1.44	−6.88***	−0.07	−0.29	−1.85	5.89***	4.41*	0.41
40–49	70 and above	−3.02	1.74	−7.42***	1.98	1.09	−0.35	4.99**	1.43	2.88
50–59	60–69	−1.86	0.38	−2.88	−0.46	0.06	2.17	5.24**	2.49	2.03
50–59	70 and above	−1.85	0.99	−4.67*	1.65	1.23	2.46	4.68*	0.18	3.83
60–69	70 and above	−0.43	0.69	−2.48	2.06	1.31	0.86	0.95	−1.52	2.37

Sample sizes are as follows: below 20 (n = 145); 20–29 (n = 717); 30–39 (n = 1,210); 40–49 (n = 1,438); 50–59 (n = 773); 60–69 (n = 457); 70 and above (n = 169). Significant differences are marked with bold for better visibility.

p < .05. **p < .01. ***p < .001.

Similarities and Differences of PEB in the Same Household

In Sample 2 (A) and (P), there was no difference between students and parents in composting, dairy/egg consumption, saving energy, using secondhand clothes, being a member of an environmental organization, participating in an environmental protest, and boycotting products made by environmental offenders. However, there were significant differences in recycling (W = 175, p = .003, rank-biserial correlation = –.528), using reusable bags (W = 1,008, p = .036, rank-biserial correlation = –.274), eating meat (W = 409, p < .001, rank-biserial correlation = –.641), using greener transportation (W = 2,225, p < .001, rank-biserial correlation = .604), and saving water (W = 1,107, p = .003, rank-biserial correlation = –.365): The students had higher scores in greener transportation, while their parents had higher scores in eating meat (namely, they ate meat less frequently), recycling, using reusable bags, and saving water.

Latent Profile Analysis

The LPA did not yield unambiguous results (Table 5). Since the LMR test was not significant at the six-profile solution, we examined the five-profile solution, which had only slightly higher AIC, BIC, and SABIC values than the six-profile solution and had the third highest entropy. These profiles were interpretable, so we analyzed this solution in more detail. The means and standard deviations of the total score of the four eco-emotion scales and z-scores of general PEB in the five profiles are presented in Table 6. It is notable that scores on all variables were linear, in the sense that they were lowest for the Lowest emotion, low PEB group and highest for the Highest anxiety, high PEB group. A group with high eco-emotions and low PEB scores did not emerge, indicating no evidence of “eco-paralysis” where strong negative eco-emotions inhibited environmental action, nor did a group with low eco-emotions and high PEB emerge.

Table 5.

Latent Profiles by Eco-Emotions and Pro-Environmental Behavior (N = 4,685).

Number of latent profiles	AIC	BIC	SABIC	Entropy	LMR	p
2	60,828.4	60,931.7	60,880.8	.764	−33,253.4	<.001
3	57,405.0	57,547.0	57,477.1	.843	−30,398.2	<.001
4	55,715.6	55,896.2	55,807.2	.832	−28,680.5	<.001
5	54,929.0	55,148.4	55,040.4	.823	−27,829.8	.012
6	54,483.6	54,741.7	54,614.6	.810	−27,430.5	.229

The best fit indices are marked with bold. AIC: Akaike information criteria; BIC: Bayesian information criteria; SABIC: sample size–adjusted Bayesian information criteria; LMR: Lo–Mendell–Rubin test; p: p value related to LMR.

Table 6.

Eco-Emotions and General PEB in the Five Profiles.

	Eco-guilt, M (SD)	Ecological grief, M (SD)	Habitual ecological worry, M (SD)	Negative consequences of anxiety, M (SD)	General PEB Z-score, M (SD)
Total sample	24.01 (6.73)	15.67 (3.78)	39.75 (7.97)	13.04 (4.16)	0.29 (0.17)
1. Lowest emotion, low PEB	13.31 (2.76)	8.26 (2.03)	20.70 (4.36)	9.26 (0.66)	−0.62 (0.82)
2. Low emotion, low PEB	19.41 (4.22)	13.18 (2.25)	34.56 (4.07)	10.18 (1.46)	−0.26 (0.84)
3. Average emotion, average PEB	25.32 (4.69)	16.71 (2.30)	42.67 (3.92)	12.20 (2.00)	0.02 (0.94)
4. Medium-high emotion, medium PEB	29.71 (4.65)	18.72 (2.49)	46.00 (4.12)	17.81 (2.06)	0.43 (1.05)
5. Highest anxiety, high PEB	34.22 (5.50)	20.97 (2.47)	49.66 (2.43)	25.20 (2.94)	1.08 (1.20)

Scores on Eco-Guilt Questionnaire could range from 11 to 44, on Ecological Grief Questionnaire from 6 to 24, on Habitual worry scale from 13 to 52, on Negative consequences of anxiety scale from 9 to 36, on General PEB Z-score from −1.71 to 4.15. General PEB: general pro-environmental behavior based on the Rasch-model. Sample sizes are N = 317, 1,374, 1,864, 952, 178, 4,685 for group 1, 2, 3, 4, 5, and for the total sample, respectively.

We named the first group, which comprised 6.9% of the participants, “Lowest emotion, low PEB” and the second group, which comprised 29.6% of the participants, “Low emotion, low PEB.” Participants in both these groups were characterized by lower-than-average level of eco-emotions and PEB but their pattern of scores differed: In the former, participants indicated that they “strongly disagreed” with most of the statements related to eco-guilt, ecological grief, and the negative consequences of anxiety, while their average responses were around the mid-point for “strongly disagree” and “somewhat disagree” in case of habitual ecological worry. They also showed the lowest frequency in general PEB. In the latter group, responses were closer to “somewhat disagree” for eco-guilt and ecological grief, “strongly disagree” for the negative consequences of anxiety, and “somewhat agree” for habitual ecological worry. The frequency of general PEB in this group was below average, but not as low as in the former group. In the third and largest group (38.9%) which we named “Average emotion, average PEB,” all the variables had average z-scores (the absolute scores were close to the total sample’s mean value, but notably this group also had low scores on the negative consequences of anxiety scale, while they experienced a moderate level of habitual ecological worry, and reported an average level of PEB). The fourth group, with 20.6% of participants, was named “Medium-high emotion, medium PEB.” In this group, the PEB scores and the scores on the eco-emotion scales were above the mean, but not the highest (the absolute scores on eco-guilt and ecological grief tended to be close to “somewhat agree,” for habitual ecological worry they were close to “strongly agree,” while for the negative consequences of anxiety, participants only “somewhat disagreed” with the statements, and the PEB level of this group was somewhat above the average level of the total sample). The fifth and smallest group (4%) was labeled “Highest anxiety, high PEB.” Participants in this group scored the highest on all five scales (the absolute scores on eco-grief and habitual ecological worry were a little higher than those for the fourth group, while they were substantially higher for eco-guilt and the negative consequences of anxiety, and the average PEB score of this group was much higher than all other groups). The z-scores of the five variables in the five latent profiles are depicted in Figure 1.

Figure 1.

Line Chart for the Latent Profiles by Eco-Emotions and Pro-Environmental Behavior (N = 4,685).

The chi-square test showed a relationship between the age groups and the latent profiles, χ²(20) = 102, p < .001. As the pairwise comparisons in Table 7 and Figure 2 indicate, in the “Lowest emotion, low PEB” profile the proportion of those in their 20s was lower than the proportion of those in their 50s. In the “Low emotion, low PEB” profile, the proportion of those in their 20s was lower than the proportion of the groups above 40, and the proportion of those below 30 was lower than the proportion of those in their 70s. In the “Medium-high emotion, medium PEB” profile, the proportion of those in their 20s was higher than the proportion of those in their 30s, 40s, and 50s. In the “Highest anxiety, high PEB” profile, the proportion of those in their 20s was higher than the proportion of those in their 40s, 50s, and 60s. The proportions of the age groups were approximately the same in the “Average emotion, average PEB” profile. However, in all cases the differences in proportions between age groups were relatively small.

Table 7.

The Associations Between Age Groups and Latent Profiles.

	Age group						Total
	Below 20 and 20–29	30–39	40–49	50–59	60–69	70 or above	Total
Profile
Lowest emotion, low PEB
Count	32_a	89_a,b	93_a,b	69_b	29_a,b	5_a,b	317
% within age group	4.3%	7.4%	6.9%	9.2%	6.4%	3.0%	6.8%
Low emotion, low PEB
Count	164_a	332_a,b	431_b,c	227_b,c	153_b,c	67_c	1374
% within age group	21.9%	27.5%	31.8%	30.4%	33.6%	39.6%	29.3%
Average emotion, average PEB
Count	301_a	485_a	528_a	317_a	174_a	59_a	1864
% within age group	40.1%	40.2%	38.9%	42.4%	38.2%	34.9%	39.8%
Medium-high emotion, medium PEB
Count	202_a	251_b	258_b	116_b	90_a,b	35_a,b	952
% within age group	26.9%	20.8%	19.0%	15.5%	19.7%	20.7%	20.3%
Highest anxiety, high PEB
Count	51_a	49_a,b	47_b	18_b	10_b	3_a,b	178
% within age group	6.8%	4.1%	3.5%	2.4%	2.2%	1.8%	3.8%
Total
Count	750	1206	1357	747	456	169	4685
% within age group	100.0%	100.0%	100.0%	100.0%	100.0%	100.0%	100.0%

Each subscript letter denotes a subset of age group categories whose column proportions do not differ significantly from each other at the .05 level (age groups with only different subscripts are significantly different at least at p < .05.). Due to the low number of participants (n = 34), the group below 20 was merged with the group 20–29 for the comparison. PEB: pro-environmental behavior (see measure in “Methods” section).

Figure 2.

The Proportion of the Age Groups in Each Latent Profile (N = 4,685).

Discussion

Generational Differences and Similarities in PEBs

The most important result of our study was the lack of general association between age and the overall PEB score, while we detected associations between age and specific PEBs: There were differences between age groups in almost all of the behaviors but with various directions and mostly a lack of linearity. These results suggest that although overall levels of PEB are not age-dependent, differently aged individuals (aging effects) or people from different generations (generational effects) may be more easily involved in different specific PEBs (Torgler & Garcia-Valinas, 2007).

While most age-related differences were small in scale, somewhat larger differences were found between age groups in green transportation, boycotting, environmental organizational membership, attending protests, the usage of reusable bags, saving water, and meat consumption. Many of these behaviors were also shown to differ among students and their parents. For other behaviors (recycling, composting, saving energy, and using secondhand clothes), differences between the age groups were very small, and there was no difference in egg/dairy consumption between the generations, nor between parent–child dyads.

Saving resources (especially water) was more common in older age groups, which is in line with previous research (Jordan, 2018; Liobikienė & Juknys, 2016; Wang et al., 2021; Wiernik et al., 2013). Somewhat surprisingly, boycotting was also more common in older generations. Harris et al. (2010) pointed out that young people seldom choose boycotts as a way of expressing their environmental concerns. It is possible that many participants in their 20s have less financial capacity to boycott certain products, compared with older adults with more stable financial backgrounds.

It seems that for some high-cost behaviors that are often linked to activism (e.g., membership in an environmental organization, participating in an environmental protest, and boycotting products) and also dairy/egg consumption and using secondhand clothes (which was quite rare in our study), family members may influence each other, as there were no differences in these behaviors within families. Grønhøj and Thøgersen (2009) similarly found that parents and their children have similar preferences for environmentally friendly products, although parents were better at sorting waste. Although parents and children did not differ in saving electricity, parents showed a higher probability of saving water, which—along with recycling—might be a less visible behavior than purchases (Grønhøj & Thøgersen, 2012).

Hence, aging effects and/or generational effects may contribute in a complex manner to the specific PEBs that individuals are motivated to perform to behave in an environmentally friendly manner. It is possible that the inconsistency in the age-related differences in this study is due to age and environmental consciousness being indeed largely unrelated. Another possibility is that age effects on different PEBs are difficult to discern because of interactions with many other influencing factors which can occur across age groups (e.g., tendency to experience negative eco-emotions, environment-related socialization, lifestyle, opportunities, knowledge; Torgler & Garcia-Valiñas, 2007).

Lessons Learned From the LPA

The LPA extended findings from previous person-centered studies in two ways: First, it examined eco-emotions and PEB in a joint model; second, it took into account the difficulty of each action (as measured by its frequency) when computing general PEB, thus avoiding overestimation of self-reported PEB actions.

Results indicated that the majority of participants were characterized by moderate levels of emotional and behavioral involvement with climate change (with more endorsement of general worry and less endorsement of more serious consequences of eco-anxiety, such as cognitive and functional impairment), while extreme levels of impairment were less frequent. The results of the LPA are in line with the results of previous studies, which found that those groups with higher environmental awareness or concern show higher behavioral involvement (Jürkenbeck et al., 2021; Kácha et al., 2022; Rhead et al., 2018). Based on findings by Heeren et al. (2022) and Innocenti et al. (2023) that higher climate change anxiety can have detrimental effects on PEBs, we expected that a latent group reflecting eco-paralysis (i.e., high anxiety with low levels of PEB) could emerge, but the results showed the opposite. In this study, the group which showed the highest ratings on negative consequences of anxiety (including both cognitive and functional impairment) (the “Highest anxiety, high PEB” group) also showed the highest level of PEB.

The results showed that young adults had a higher probability of belonging to the medium/higher anxiety groups (which were characterized by relatively high levels of worry, moderate or high levels of eco-guilt and eco-grief, and where negative consequences of anxiety were also reported) than the older generations, except for those in their 70s (although this age group was too small to draw firm conclusions). This result is in line with previous studies (e. g., Clayton & Karazsia, 2020; Hawcroft & Milfont, 2010; Heeren et al., 2022; Kácha et al., 2022). This may account for the lack in engagement of middle-aged people with some pro-environmental activities. An explanation of the lower eco-emotions among adults between 30 and 70 could be that people in this age group are often breadwinners for their family and hence may have less time and energy to contemplate any issue not directly related to their family or work-related everyday obligations. Consequently, they may more neglect environmental issues with longer term consequences and experience weaker eco-emotions than people in their 20s who are in the phase of exploring the world and society.

Our results suggest that eco-emotions play a crucial role in the realization of PEBs, as in our sample, the higher the negative emotions, the higher the PEBs were. This suggests that eco-emotions are important prerequisites of higher PEBs, which may be enacted as a means of coping with these negative emotions.

Limitations and Future Directions

There were some limitations in sampling and data collection in this study. Due to the pandemic, there was online education in secondary schools during the data collection period, which resulted in a lower sample size in Sample 2 (A) and (P) than anticipated. Although Sample 1 was sufficiently large, biases may have arisen due to the recruitment method. The link to the questionnaire was published by an independent news portal that regularly publishes news in a wide range of genres (e.g., national and international political news, comprehensive reports on various social trends and issues, science-related articles, and tabloids) and whose readership, as reflected in Table 2, is largely comprised of highly educated men living in the capital, which may have influenced the response patterns.

Because eco-emotions and behaviors were self-reported, some may have been inaccurately reported, for example, participants may have tended to overestimate socially desirable actions such as PEBs, or under-reported their emotional reactions. Future research should attempt to use more objective measures.

While our data indicate differences in emotions and PEBs across age groups, it cannot ascertain whether these are due to aging or generational effects. Longitudinal designs would be needed to examine this question. Other important areas for further study include assessing the interactions of these eco-emotions and PEBs with age, personality, the sense of control, other eco-emotions like eco-anger and social status, and determining the efficiency of environmental awareness-raising attempts in the different segments of society. To engage all segments of society in adopting sustainable lifestyles, we need to know, for example, the motivations and barriers to enacting PEBs (including the role of eco-emotions) for people varying in age, personality, gender, and social status.

Our study may encourage more nuanced communication regarding pro-environmental actions, which avoids simplified and generalized statements about generational differences in environmental behavior, emphasizes the opportunities and limits that everybody has regarding PEBs, and offers a broad range of effective PEBs that can be adopted. Future research could examine how efforts at raising environmental awareness could be differentiated according to the different eco-emotions, PEBs patterns, social environment, and lifestyles of different generations.

Conclusions

In summary, our results indicate that different profiles of eco-emotions and PEB can be identified, with increasing emotional concern being reflected in more PEB. Different age groups tend to adopt differing PEBs, and parents and children share some but not all such behaviors. This suggests the value of addressing various behaviors separately, both in research and in targeted environmental communication.

Our results also indicate that besides (or instead of) considering eco-anxiety as a mental health issue, at nonclinical levels it can be considered a starting point for the promotion of PEBs. Further studies should define the forms and levels of eco-anxiety which require psychological help and reveal the optimal ways to turn nonclinical forms of eco-anxiety into PEBs and enhance people’s psychological well-being at the same time.

Supplemental Material

sj-docx-1-jbd-10.1177_01650254231222436 – Supplemental material for Age differences and profiles in pro-environmental behavior and eco-emotions

Supplemental material, sj-docx-1-jbd-10.1177_01650254231222436 for Age differences and profiles in pro-environmental behavior and eco-emotions by Csilla Ágoston, Bernadett Balázs, Ferenc Mónus and Attila Varga in International Journal of Behavioral Development

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The first and the fourth author’s work was supported by the European Climate Foundation (grant number: G-2110-62765). The first author was supported by the 2021 Science Patronage call funded by the National Research, Development and Innovation Fund (grant number: MEC_R 141568). The funding institutions had no role in the study design or the data collection, analysis, and interpretation of the data; writing the manuscript; or the decision to submit the paper for publication.

Statement of Ethics

The authors complied with APA ethical standards in the treatment of the participants and the studies were approved by the Research Ethics Committee of the Faculty of Education and Psychology, ELTE Eötvös Loránd University (number of the ethical approval: 2020/481).

ORCID iD

Csilla Ágoston

Supplemental Material

Supplemental material for this article is available online.

Notes

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