Validity of implicit measures of environmental attitudes
| Název práce v češtině: | Validita implicitních měření environmentálních postojů |
|---|---|
| Název v anglickém jazyce: | Validity of implicit measures of environmental attitudes |
| Klíčová slova: | implicitní měření, explicitní měření, test implicitních asociací (IAT), environmentální postoje, sekundární analýza dat |
| Klíčová slova anglicky: | implicit measures, explicit measures, implicit association test (IAT), environmental attitudes, secondary data analysis |
| Akademický rok vypsání: | 2022/2023 |
| Typ práce: | bakalářská práce |
| Jazyk práce: | angličtina |
| Ústav: | Katedra sociologie (23-KS) |
| Vedoucí / školitel: | doc. Mgr. Jan Urban, Ph.D. |
| Řešitel: | skrytý - zadáno vedoucím/školitelem |
| Datum přihlášení: | 25.09.2023 |
| Datum zadání: | 25.09.2023 |
| Datum a čas obhajoby: | 09.09.2025 09:00 |
| Místo konání obhajoby: | Areál Jinonice, B216, 216, seminární místnost ISS |
| Datum odevzdání elektronické podoby: | 29.07.2025 |
| Datum proběhlé obhajoby: | 09.09.2025 |
| Oponenti: | Ewa Małgorzata Duda |
| Seznam odborné literatury |
| Belletier, C., Robert, A., Moták, L., & Izaute, M. (2018). Toward explicit measures of intention to predict information system use: An exploratory study of the role of implicit attitudes. Computers in Human Behavior, 86, 61–68. https://doi.org/10.1016/j.chb.2018.04.029
Brügger, A., Kaiser, F. G., & Roczen, N. (2011). One for All? European Psychologist, 16(4), 324–333. https://doi.org/10.1027/1016-9040/a000032 Dunlap, R. E., & Van Liere, K. D. (1978). The “New Environmental Paradigm.” The Journal of Environmental Education, 9(4), 10–19. https://doi.org/10.1080/00958964.1978.10801875 Fiorenza, M., Duradoni, M., Barbagallo, G., & Guazzini, A. (2023). Implicit association test (IAT) toward climate change: A PRISMA systematic review. Current Research in Ecological and Social Psychology, 4, 100103. https://doi.org/10.1016/j.cresp.2023.100103 Geng, L., Xu, J., Ye, L., Zhou, W., & Zhou, K. (2015). Connections with Nature and Environmental Behaviors. PLoS ONE, 10(5), 1–11. https://doi.org/10.1371/journal.pone.0127247 Greenwald, A. G., & Banaji, M. R. (1995). Implicit social cognition: Attitudes, self-esteem, and stereotypes. Psychological Review, 102(1), 4–27. https://doi.org/10.1037/0033-295X.102.1.4 Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74(6), 1464–1480. https://doi.org/10.1037//0022-3514.74.6.1464 Kaiser, F. (1998). A General Measure of Ecological Behavior1. Journal of Applied Social Psychology, 28, 395–422. https://doi.org/10.1111/j.1559-1816.1998.tb01712.x Levine, D. S., & Strube, M. J. (2012). Environmental attitudes, knowledge, intentions and behaviors among college students. The Journal of Social Psychology, 152(3), 308–326. https://doi.org/10.1080/00224545.2011.604363 McGuire, L., & Beattie, G. (2019). Talking green and acting green are two different things: An experimental investigation of the relationship between implicit and explicit attitudes and low carbon consumer choice. Semiotica, 2019(227), 99–125. https://doi.org/10.1515/sem-2017-0138 Milfont, T. L., & Duckitt, J. (2010). The environmental attitudes inventory: A valid and reliable measure to assess the structure of environmental attitudes. Journal of Environmental Psychology, 30(1), 80–94. https://doi.org/10.1016/j.jenvp.2009.09.001 Nosek, B. A., Greenwald, A. G., & Banaji, M. R. (2007). The Implicit Association Test at Age 7: A Methodological and Conceptual Review. In Social psychology and the unconscious: The automaticity of higher mental processes (pp. 265–292). Psychology Press. Nosek, B. A., Smyth, F. L., Hansen, J. J., Devos, T., Lindner, N. M., Ranganath, K. A., Smith, C. T., Olson, K. R., Chugh, D., Greenwald, A. G., & Banaji, M. R. (2007). Pervasiveness and correlates of implicit attitudes and stereotypes. European Review of Social Psychology, 18(1), 36–88. https://doi.org/10.1080/10463280701489053 Panzone, L., Hilton, D., Sale, L., & Cohen, D. (2016). Socio-demographics, implicit attitudes, explicit attitudes, and sustainable consumption in supermarket shopping. Journal of Economic Psychology, 55, 77–95. https://doi.org/10.1016/j.joep.2016.02.004 Sánchez, M. P., de la Garza González, A., & Hedlefs, M. I. (2016). Implicit measures of environmental attitudes: A comparative study. International Journal of Psychological Research, 9(1), 40–51. https://doi.org/10.21500/20112084.2099 Schultz, P. W., Shriver, C., Tabanico, J. J., & Khazian, A. M. (2004). Implicit connections with nature. Journal of Environmental Psychology, 24(1), 31–42. https://doi.org/10.1016/S0272-4944(03)00022-7 Schultz, P. W., & Tabanico, J. (2007). Self, identity, and the natural environment: Exploring implicit connections with nature. Journal of Applied Social Psychology, 37(6), 1219–1247. https://doi.org/10.1111/j.1559-1816.2007.00210.x Sun, Y., Li, Y., Cai, B., & Li, Q. (2020). Comparing the explicit and implicit attitudes of energy stakeholders and the public towards carbon capture and storage. Journal of Cleaner Production, 254, 120051. https://doi.org/10.1016/j.jclepro.2020.120051 |
| Předběžná náplň práce |
| There are various ways of measuring environmental attitude, most studies use explicit measures, mainly self-report methods – for example the GEB scale (Kaiser, 1998), which has the following scopes of action: Energy saving, Mobility, Waste avoidance, Consumption, Recycling and Social engagement. Another well-used measure is the NEP scale, which also uses general topics of environmental attitude (Dunlap & Van Liere, 1978). However, not all aspects of attitudes in general are accessible via explicit measures, therefore some studies use implicit measures of attitudes, which reveal associative information people might not be conscious of or are unwilling to report (Nosek et al., 2007). The most common method for measuring them is the Implicit Attitudes Test, or IAT for short. It measures the degree of association between concepts (such as vegetarian products, public transport, black people, or thinness) and various classifications or stereotypes (such as good and bad, or handy and clumsy) (Greenwald et al., 1998).
Outside of environmental attitude research, implicit measures are widely used and successful in terms of predictive and discriminant validity. Many research has been done regarding racial/ethnic bias – a study by McConnell and Leibold found that participants who had stronger negative attitudes towards Black (versus Whites) on the IAT also had stronger negative attitudes on the explicit measures while also having more negative social interactions with Blacks (McConnell & Leibold, 2001). However, in terms of environmental attitudes, this has not been the case. A recent systematic review of IAT-based measures in the environmental domain revealed that implicit and explicit attitudes toward “climate change” appeared unrelated, whereas the relationship between IAT and climatic beliefs was inconsistent across studies (Fiorenza et al., 2023). These inconsistencies persist in more general research of environmental attitude, which may be issue. Some studies also discuss whether IAT can or cannot predict specific pro-environmental behavior. Results of a recent research (which examined implicit attitudes, explicit attitudes and “green” consumption in supermarket shopping) suggest that implicit attitudes towards environmentally friendly food are not always associated with sustainable consumption (Panzone et al., 2016). Another study examined the relationship between connection with nature and pro-environmental behavior. The results of the study showed that explicit connection with nature was positively correlated with intentional environmental behavior, and implicit connection with nature was positively correlated with spontaneous environmental behavior. However, implicit and explicit connections with nature were independent of each other (Geng et al., 2015). A different study investigated the relationship between explicit and implicit attitudes towards carbon footprint and self-reported environmental behavior and low-carbon choices. Results indicated that self-report attitudes toward carbon footprint were only associated with self-report environmental behavior. However, self-report attitudes were not significantly associated with the choice of low-carbon alternatives in the simulated purchases. Most studies work with self-report environmental attitudes, so the authors suggest that research results may indicate environmental attitude bias. They also did not find a significant association for implicit attitudes, but respondents with strong implicit attitudes towards low-carbon economy chose more low-carbon items, but only under time pressure. Without time pressure, the opposite trend was found for explicit attitudes (McGuire & Beattie, 2019). On the contrary, some studies have shown a positive association of explicit and implicit measures. One of them argues that individuals have environmental attitudes based on how much they consider themselves to be part of nature. Its results indicate a moderate association even in a replicated study (Schultz et al., 2004). Most studies use more general scales of environmental attitude, which may be the reason for low predictive and discriminant validity. In my research, I will focus on a specific area – in other studies of attitude, researchers have focused on more specific things (for example racism towards a specific ethnic group), while environmental attitude is a much broader topic. I will try to discover how implicit measures work in different contexts of generality, by focusing on a specific area (for example food consumption or transport). The purpose of this work is to explore the predictive and discriminant validity of IATs in the context of pro-environmental behavior (to what extent can IAT predict other constructs and how does differ from these construct) and to explain why IATs do not work well in the environmental field. Method We have already done a pilot study on a small sample with some colleagues as a part of The Practice in Quantitative Research course. The study had interesting results, showing that explicit environmental attitude significantly correlates with implicit environmental attitude (which other studies failed to prove). I will then do a systematic review of pertinent literature and formulate hypotheses why IAT works or does not work in the environmental field. Next step will be the main study, which will be conducted on a larger sample of participants within a study run by my supervisor. The analytical methods this study will use will be correlational analysis and/or regression analysis. |
| Předběžná náplň práce v anglickém jazyce |
| There are various ways of measuring environmental attitude, most studies use explicit measures, mainly self-report methods – for example the GEB scale (Kaiser, 1998), which has the following scopes of action: Energy saving, Mobility, Waste avoidance, Consumption, Recycling and Social engagement. Another well-used measure is the NEP scale, which also uses general topics of environmental attitude (Dunlap & Van Liere, 1978). However, not all aspects of attitudes in general are accessible via explicit measures, therefore some studies use implicit measures of attitudes, which reveal associative information people might not be conscious of or are unwilling to report (Nosek et al., 2007). The most common method for measuring them is the Implicit Attitudes Test, or IAT for short. It measures the degree of association between concepts (such as vegetarian products, public transport, black people, or thinness) and various classifications or stereotypes (such as good and bad, or handy and clumsy) (Greenwald et al., 1998).
Outside of environmental attitude research, implicit measures are widely used and successful in terms of predictive and discriminant validity. Many research has been done regarding racial/ethnic bias – a study by McConnell and Leibold found that participants who had stronger negative attitudes towards Black (versus Whites) on the IAT also had stronger negative attitudes on the explicit measures while also having more negative social interactions with Blacks (McConnell & Leibold, 2001). However, in terms of environmental attitudes, this has not been the case. A recent systematic review of IAT-based measures in the environmental domain revealed that implicit and explicit attitudes toward “climate change” appeared unrelated, whereas the relationship between IAT and climatic beliefs was inconsistent across studies (Fiorenza et al., 2023). These inconsistencies persist in more general research of environmental attitude, which may be issue. Some studies also discuss whether IAT can or cannot predict specific pro-environmental behavior. Results of a recent research (which examined implicit attitudes, explicit attitudes and “green” consumption in supermarket shopping) suggest that implicit attitudes towards environmentally friendly food are not always associated with sustainable consumption (Panzone et al., 2016). Another study examined the relationship between connection with nature and pro-environmental behavior. The results of the study showed that explicit connection with nature was positively correlated with intentional environmental behavior, and implicit connection with nature was positively correlated with spontaneous environmental behavior. However, implicit and explicit connections with nature were independent of each other (Geng et al., 2015). A different study investigated the relationship between explicit and implicit attitudes towards carbon footprint and self-reported environmental behavior and low-carbon choices. Results indicated that self-report attitudes toward carbon footprint were only associated with self-report environmental behavior. However, self-report attitudes were not significantly associated with the choice of low-carbon alternatives in the simulated purchases. Most studies work with self-report environmental attitudes, so the authors suggest that research results may indicate environmental attitude bias. They also did not find a significant association for implicit attitudes, but respondents with strong implicit attitudes towards low-carbon economy chose more low-carbon items, but only under time pressure. Without time pressure, the opposite trend was found for explicit attitudes (McGuire & Beattie, 2019). On the contrary, some studies have shown a positive association of explicit and implicit measures. One of them argues that individuals have environmental attitudes based on how much they consider themselves to be part of nature. Its results indicate a moderate association even in a replicated study (Schultz et al., 2004). Most studies use more general scales of environmental attitude, which may be the reason for low predictive and discriminant validity. In my research, I will focus on a specific area – in other studies of attitude, researchers have focused on more specific things (for example racism towards a specific ethnic group), while environmental attitude is a much broader topic. I will try to discover how implicit measures work in different contexts of generality, by focusing on a specific area (for example food consumption or transport). The purpose of this work is to explore the predictive and discriminant validity of IATs in the context of pro-environmental behavior (to what extent can IAT predict other constructs and how does differ from these construct) and to explain why IATs do not work well in the environmental field. Method We have already done a pilot study on a small sample with some colleagues as a part of The Practice in Quantitative Research course. The study had interesting results, showing that explicit environmental attitude significantly correlates with implicit environmental attitude (which other studies failed to prove). I will then do a systematic review of pertinent literature and formulate hypotheses why IAT works or does not work in the environmental field. Next step will be the main study, which will be conducted on a larger sample of participants within a study run by my supervisor. The analytical methods this study will use will be correlational analysis and/or regression analysis. |