Environmental psychology perspective on mitigating environmental pollution: from perceptions to behavioural outcomes

Environmental psychology perspectives on mitigating environmental pollution: from perceptions to behavioural outcomes Valeria Vitale, Nina Vaupotič, Sabine Pahl Environmental Psychology Group • Department of Cognition, Emotion, and Methods • Faculty of Psychology • https://env-psy.univie.ac.at/ Systems view of pollutants & society Predictors of action A few words on analytical approaches Establish levels of, e.g., risk perception, affect, intentions Establish predictors of these; explain underlying factors Establish relative importance (typically no absolute measurement) Understand pathways to e.g. risk perceptions; modelling complexity E.g., affect predicts policy support but only through risk perception (mediation) E.g., association between risk perception and policy support only for people high in biospheric values (moderation) Understand the Psychology of risk Use in communication and for “people” interventions Today •Systems perspective •SOSZEROPOL2030 sister project •Study 1: Risk perception •Study 2: Behaviour Intentions •Conclusions SOSZEROPOL2030 Methodology SOS-ZEROPOL –focus on 4 marine pollutants •Potential negative effects on natural environments and human health. •High degree of product dependence in our society. •Scientific uncertainty and manufactured doubt (Oreskes and Conway, 2010). Microplastics PFAS (per-and polyfluoroalkyl substances) Nutrients pollution Underwater noise Sample and method Nationally representative samples Online survey between November 2023 and January 2024 Survey procedure POLLUTANT SPECIFIC FACTORS PSYCHOLOGICAL FACTORS PSYCHOLOGICAL FACTORS POLLUTANT SPECIFIC FACTORS Have you ever been directly affected by the pollutant in your everyday life? Vaupotič et al. (in preparation) Have you ever been directly affected by the pollutant in your everyday life? Vaupotič et al. (in preparation) RISK PERCEPTION INDEX (combined) How concerned are you personally about the effects of microplastics on human health? How concerned are you personally about the effects of microplastics on the environment (nature, animals)? In the context of all the pressing issues society is facing (social, economic, environmental), how urgent is it to tackle microplastics pollution? How concerned are citizens about environmental pollution? Mean and distribution of risk perception score of microplastics, PFAS, nutrients and underwater noise including error bars, box plots and pair-wise t-statistics T(4375) = 53.03, p < 0.001 T(4629) = 12.00, p < 0.001 T(4206) = 25.50, p < 0.001 T(4526) = 31.40, p < 0.001 Vaupotič et al. (in preparation) Predictor estimates of risk perception for each pollutant (95% CI) Adj. R2: 0.51 Adj. R2: 0.48 Adj. R2: 0.43 Adj. R2: 0.42 Multilevel regression models accounting for country belonging Vaupotič et al. (in preparation) The relative importance of each predictor across environmental pollutants’ risk perception models Relative weights analysis estimating the relative importance of each predictor based on ordinary least squares regression.  Ordered according to importance of microplastics risk perception. Vaupotič et al. (in preparation) Discussion Risk perception of environmental pollutants is shaped by both person-level (e.g., values, affect, knowledge) and pollutant-level factors. Biospheric values, pro-environmental norms, negative affect, subjective knowledge, experience, trust, and systems thinking are consistently related to risk perception of pollutants Valeria looks into the relationships between these variables. Communication strategies could raise awareness about lesser-known pollutants (e.g., PFAS, underwater noise, nutrients). The public perceives microplastics as riskier than PFAS, despite greater scientific certainty about PFAS’s harms Possibly because microplastics has been a topic of research and media for longer? Vaupotič et al. (in preparation) Study 2: Behavioral intentions Vitale et al. (in preparation) •Pollution threatens ecosystems, human health, and societal well-being •Understanding psychological drivers of pro-environmental behavior is crucial for effective interventions •Research increasingly highlights cognitive, normative, and affective processes as determinants of behaviors •Value-Belief-Norm (VBN, Stern et al., 1999) theory: values → beliefs → personal norms → behavior Study 2 – Integrating experiential factors into the VBN framework predicting behavioral intentions VALUES BELIEFS NORMS BEHAVIORS Figure 1. Schematic model of variables in the Value-Belief-Norm theory as applied to environmentalism (Stern, 1999) VBN framework Egoistic values Biospheric values Altruistic values New ecological paradigm Awareness of consequences Ascription of responsability Pro-environmental personal norm Environmental activism Environmental citizenship Policy support Private-sphere behaviors VALUES BELIEFS NORMS BEHAVIORS Figure 1. Schematic model of variables in the Value-Belief-Norm theory as applied to environmentalism (Stern, 1999) VBN framework Egoistic values Biospheric values Altruistic values New ecological paradigm Awareness of consequences Ascription of responsability Pro-environmental personal norm Environmental activism Environmental citizenship Policy support Private-sphere behaviors AFFECTIVE PROCESSING AFFECT refers to the positive or negative feelings toward something, which serve as quick evaluation heuristics that inform judgments and decisions (Slovic et al., 2007) PERSONAL EXPERIENCE plays a crucial role in shaping individuals’ perceptions and judgments, and serves as a foundation for affective responses (Damasio, 1994; Risen & Critcher, 2011; Weber, 2006) + H4 Egoistic values Risk perception (pollutant-specific) Negative holistic affect (pollutant-specific) Behavioral intentions Biospheric values Altruistic values Personal norm + H1a Personal experience (pollutant-specific) - H1b + H1c + H2 + H3 + H5 VALUES NORMS BEHAVIORSAFFECT BELIEFS Figure 2. Conceptual serial mediation model of the extended VBN theory, with hypothesized paths Extended VBN I intend to vote for parties with a strong environmental agenda I intend to pay more attention to my own consumer behaviour I intend to support or sign petitions with an environmental agenda Vitale et al. (in preparation) + H4 Egoistic values Risk perception (pollutant-specific) Negative holistic affect (pollutant-specific) Behavioral intentions Biospheric values Altruistic values Personal norm + H1a Personal experience (pollutant-specific) - H1b + H1c + H2 + H3 + H5 VALUES NORMS BEHAVIORSAFFECT BELIEFS Figure 2. Conceptual serial mediation model of the extended VBN theory, with hypothesized paths Extended VBN Vitale et al. (in preparation) •Intention to vote for parties was significantly lower than both own consumption (-0.793, p < .001) and support petitions (-0.064, p = .007) •Own consumption intentions were significantly higher than support petitions (0.729, p < .001). •Overall, participants reported the strongest intentions for changing their own consumption, followed by supporting petitions, and the lowest for voting for proenvironmental parties. Figure 3. Behavioral intentions’ responses across countries, with significant comparisons Results –Descriptives for behaviors 7 6 5 4 3 2 1 Vitale et al. (in preparation) •There are differences across countries •Participants in Bulgaria, Greece and Ireland expressed higher intentions to engage in environmentally supportive behaviors •Participants in Belgium and the Netherlands generally reported lower levels of intentions to engage in environmentally supportive behaviors Figure 4. Composite behavioral intentions’ scores across countries, with significant comparisons Results –Descriptives for behaviors Vitale et al. (in preparation) Figure 5. Heatmap representing the correlation matrix between key variables Results –Correlations across variables of interest Vitale et al. (in preparation) .28* Egoistic values Risk perception (pollutant-specific) Negative holistic affect (pollutant-specific) Behavioral intentions Biospheric values Altruistic values Personal norm .25* Personal experience (pollutant-specific) - .13* ~ .37* .31* VALUES NORMS BEHAVIORSAFFECT BELIEFS Figure 6. Results of the serial mediation model (RQ1) of the extended VBN theory, with standardized coefficients .09* R = .34 * R = .43 * R = .38 * R = .54 * p <.001 •More personal experience with all pollutants (ref. don’t know) → more negative affect ~ * RQ1 –Overall mediation paths (4 pollutants)Vitale et al. (in preparation) .28* Egoistic values Risk perception (pollutant-specific) Negative holistic affect (pollutant-specific) Behavioral intentions Biospheric values Altruistic values Personal norm .25* Personal experience (pollutant-specific) - .13* ~ .37* .31* VALUES NORMS BEHAVIORSAFFECT BELIEFS Figure 6. Results of the serial mediation model (RQ1) of the extended VBN theory, with standardized coefficients .09* R = .34 * R = .43 * R = .38 * R = .54 * p <.001 * RQ1 –Overall mediation paths (4 pollutants) •Significant indirect effects values → affect → beliefs → norms → behavior experience → affect → beliefs → norms → behavior Vitale et al. (in preparation) .28* Egoistic values Risk perception (pollutant-specific) Negative holistic affect (pollutant-specific) Behavioral intentions Biospheric values Altruistic values Personal norm .25* Personal experience (pollutant-specific) - .13* ~ .37* .31* VALUES NORMS BEHAVIORSAFFECT BELIEFS Figure 6. Results of the serial mediation model (RQ1) of the extended VBN theory, with standardized coefficients .09* R = .34 * R = .43 * R = .38 * R = .54 * p <.001 Positive significant direct effects Non-significant direct effects * RQ1 –Overall mediation paths (4 pollutants)Vitale et al. (in preparation) .28* Egoistic values Risk perception (pollutant-specific) Negative holistic affect (pollutant-specific) Behavioral intentions Biospheric values Altruistic values Personal norm .25* Personal experience (pollutant-specific) - .13* ~ .37* .31* VALUES NORMS BEHAVIORSAFFECT BELIEFS Figure 6. Results of the serial mediation model (RQ1) of the extended VBN theory, with standardized coefficients .09* R = .34 * R = .43 * R = .38 * R = .54 * p <.001 Positive significant direct effects Non-significant direct effects * RQ1 –Overall mediation paths (4 pollutants) •The model accounts for a great proportion of explained variance in all key constructs Vitale et al. (in preparation) .43* .41* Egoistic values Negative holistic affect (PFAS) Biospheric values Altruistic values Personal experience (PFAS) VALUES AFFECT R = .34 * Negative holistic affect (microplastics) Personal experience (microplastics) Risk perception (PFAS) Risk perception (microplastics) Personal norm Behavioral intentions .33* R = .51 * R = .36 * R = .41 * R = .39 *R = .16 * R = .21 * NORMS BEHAVIORS BELIEFS +* +* Figure 7. Results of the serial mediation model across pollutants (RQ2) of the extended VBN theory, with standardized coefficients * p <.001 RQ2 –Across 2 pollutants: microplastics and PFAS Vitale et al. (in preparation) Conclusions •Environmental psychology perspective (~ Social/Behavioural Science) •Risk perception driven by affect, values, norms •Adding affect improves predictions of behavioural outcomes •Strengths: Large, representative samples; good statistical power, open Science, e.g., preregistrations •Limitations: Cross-sectional data, self-report •Risk to success of “solutions”, trust, reputation, if human response is not taken into account •Let’s work together across disciplines and sectors THANK YOU FOR LISTENING! Contacts: https://soszeropol2030.eu/# https://zeropm.eu/ https://env-psy.univie.ac.at/ https://ech.univie.ac.at/ Prof. Sabine PahlDr. Nina Vaupotič Dr. Valeria Vitale