The Attentional Bias Toward Images of Climate Change and Its Impact on Citizen Commitment
DOI:
https://doi.org/10.5294/pacla.2024.27.4.5Keywords:
Attention, climate change, images, environment, perceptionAbstract
Visual communication may influence public perception of the climate crisis. This study examines how attentional bias toward climate change-related images is associated with pro-environmental attitudes. A self-report approach was employed with 312 university students exposed to negative, positive, and neutral pieces, finding that their emotional valence plays a crucial role in shaping risk perception. Images highlighting environmental and economic losses tend to attract attention; however, they can also discourage deeper reflection on individual contributions to the issue. In contrast, positive images encourage people to think critically and propose solutions. The study shows that the public’s ability to visualize short-term goals and successes leads to a greater willingness to support environmental initiatives. These findings provide evidence on the images that should be used to promote citizen commitment to combat climate change. It is not advisable to transmit disturbing or fear-inducing images, as they may trigger defensive psychological responses and deter audiences from engaging with environmental issues.
Downloads
References
Alexa (2023). The top 500 sites on the web. https://www.alexa.com/topsites
American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders. https://doi.org/10.1176/appi.books.9780890425596
Anwar, R. (2023). The emotional and behavioral effects of youth exposure to images of the global climate change crisis and its relationship to their personal characteristics Quasi-experimental study. Journal of Mass Communication Research, 68(1), 3-110. https://doi.org/10.21608/jsb.2023.323785
Bendall, R., Begley, S. y Thompson, C. (2021). Interactive influences of emotion and extraversion on visual attention. Brain and Behavior, 11, e2387. https://doi.org/10.1002/brb3.2387
Bord, R., Fisher, A. y O’Connor, R. (1998). Public perceptions of global warming: United States and international perspectives. Climate Research, 11, 75-84. https://doi.org/10.3354/cr011075
Bradley, M., Sabatinelli, D., Lang, P., Fitzsimmons, J., King, W. y Desai, P. (2003). Activation of the visual cortex in motivated attention. Behavioral Neuroscience, 117(2), 369-380. https://doi.org/10.1037/0735-7044.117.2.369
Carlson, J., Kaull, H., Steinhauer, M., Zigarac, A. y Cammarata, J. (2020). Paying attention to climate change: Positive images of climate change solutions capture attention. Journal of Environmental Psychology, 71, 101477. https://doi.org/10.1016/j.jenvp.2020.101477
Chapman, D., Corner, A., Webster, R. y Markowitz, E. (2016). Climate visuals: A mixed methods investigation of public perceptions of climate images in three countries. Global Environmental Change, 41, 172-182. https://doi.org/10.1016/j.gloenvcha.2016.10.003
Cook, J. y Lewandowsky, S. (2016). Rational irrationality: Modeling climate change belief polarization using bayesian networks. Topics in Cognitive Science, 8, 160-179. https://doi.org/10.1111/tops.12186
Desnoyers, L. (2011). Toward a taxonomy of visuals in science communication. Technical Communication, 58(2), 119-134.
Dixon, G., McKeever, B., Holton, A., Clarke, C. y Eosco, G. (2015). The power of a picture: overcoming scientific misinformation by communicating weight-of-evidence information with visual exemplars. Journal of Communication, 65(4), 639-659. https://doi.org/10.1111/jcom.12159
Doyle, J. (2007). Picturing the clima(c)tic: Greenpeace and the representational politics of climate change communication. Science as Culture, 16(2), 129-150. https://doi.org/10.1080/09505430701368938
Duan, R., Takahashi, B. y Zwickle, A. (2021). How effective are concrete and abstract climate change images? The moderating role of construal level in climate change visual communication. Science Communication, 43(3), 358-387. https://doi.org/10.1177/10755470211008192
Erviti, M. C. (2013). Las imágenes del cambio climático en los informativos de televisión. Análisis de seis televisiones españolas de cobertura nacional. [Tesis doctoral, Universidad de Navarra]. http://dadun.unav.edu/handle/10171/39019
Fox, E., Mathews, A., Calder, A. y Yiend, J. (2007). Anxiety and sensitivity to gaze direction in emotionally expressive faces. Emotion, 7(3), 478-486. https://doi.org/10.1037/1528-3542.7.3.478
Fredrickson, B. y Branigan, C. (2005). Positive emotions broaden the scope of attention and thought-action repertoires. Cognition & emotion, 19(3), 313-332. https://doi.org/10.1080/02699930441000238
Fredrickson, B. y Branigan, C. (2001). Positive emotions. En Mayne, T. y Bonnano, G. (eds.), Emotion: Current issues and future directions (pp. 123-151). Guilford Press.
Fredrickson, B. (2001). The role of positive emotions in positive psychology. The broaden-and-build theory of positive emotions. The American Psychologist, 56(3), 218-226. https://doi.org/10.1037//0003-066X.56.3.218
Ghoushchi, S., Yazdani, H., Dowlatabadi, H. y Ahmadian, M. (2021). A multimodal discourse analysis of pictures in ELT textbooks: Modes of communication in focus. Jordan Journal of Modern Languages and Literatures, 13(4), 623-644. https://doi.org/10.47012/jjmll.13.4.2
Gigante, M. (2012). Accommodating scientific illiteracy: Award-winning visualizations on the covers of Science. Journal of Technical Writing and Communication, 42(1), 21-38. https://doi.org/10.2190/TW.42.1.c
Heim, M. (1998). Virtual realism. Oxford University Press.
Kaltenborn, B. y Bjerke, T. (2002). Association between environmental value orientations and landscape preferences. Landscape and Urban Planning, 59(1), 1-11. https://doi.org/10.1016/S0169-2046(01)00243-2
Kahn-Harris, K. (2018). Denialism: What drives people to reject the truth. The Guardian, 3 de agosto. https://www.theguardian.com/news/2018/aug/03/denialism-what-drives-people-to-reject-the-truth
Lane, R., Chua, P. y Dolan, R. (1999). Common effects of emotional valence, arousal and attention on neural activation during visual processing of pictures. Neuropsychologia, 37(9), 989-997. https://doi.org/10.1016/S0028-3932(99)00017-2
Lehman, B., Thompson, J., Davis, S. y Carlson, J. (2019). Affective images of climate change. Frontiers in Psychology, 10, 1-10. https://doi.org/10.3389/fpsyg.2019.00960
Leiserowitz, A. (2005). American risk perceptions: Is climate change dangerous? Risk Analysis: An International Journal, 25(6), 1433-1442. https://doi.org/10.1111/j.1540-6261.2005.00690.x
León, B., Negredo, S. y Erviti, M. C. (2022). Social engagement with climate change: Principles for effective visual representation on social media. Climate Policy, 1-17. https://doi.org/10.1080/14693062.2022.2077292
Le Meur, O., Le Callet, P., Barba, D. y Thoreau, D. (2006). A coherent computational approach to model the bottom-up visual attention. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(5), 802-817. https://doi.org/10.1109/TPAMI.2006.86
Lombard, M., Reich, R., Grabe, M., Bracken, C. y Ditton, T. (2000). Presence and television: The role of screen size. Human Communication Research, 26(1), 75-98. https://doi.org/10.1111/j.1468-2958.2000.tb00750.x
Luna, D., Bering, J. y Halberstadt, J. (2022). The value and distinctiveness of awe in science communication: Comparing the incidence and content of ‘awesome’ representations in science and non-science picture books. International Journal of Science Education, 12(2), 143-156. https://doi.org/10.1080/21548455.2022.2048119
Luo, Y. y Zhao, J. (2019). Motivated attention in climate change perception and action. Frontiers in Psychology, 10, 1-13. https://doi.org/10.3389/fpsyg.2019.01541
Manzo, K. (2010). Imaging vulnerability: The iconography of climate change. Area, 42(1), 96-107. https://doi.org/10.1111/j.1475-4762.2009.00887.x
Markowtiz, E., Slovic, P., Vastfjall, D. y Hodges, S. (2013). Compassion fade and the challenge of environmental conservation. Judgment and Decision Making, 8(4), 397-406. https://doi.org/10.1017/S193029750000526X
Mayer, J., Salovey, P. y Caruso, D. (2004). Emotional intelligence: Theory, findings, and implications. Psychological Inquiry, 15(3), 197-215. https://doi.org/10.1207/s15327965pli1503_02
Min, X., Zhai, G., Gu, K., Liu, J., Wang, S., Zhang, X. y Yang, X. (2017). Visual attention analysis and prediction on human faces. Information Sciences, 420, 417-430. https://doi.org/10.1016/j.ins.2017.08.040
Muñoz-Pico, H. P. y Viteri-Mancero, F. (2022). Del ver al compartir: el rol de las emociones en la propagación de contenidos sobre cambio climático en YouTube. Palabra Clave, 25(2), e2526. https://doi.org/10.5294/pacla.2022.25.2.6
Muñoz-Pico, H. P., León, B. y García-Martínez, A. N. (2021). Representación del cambio climático en YouTube: un análisis cuantitativo de los vídeos más populares. Palabra Clave, 24(1), e2415. https://doi.org/10.5294/pacla.2021.24.1.5
Nicholson-Cole, S. (2005). Representing climate change futures: A critique on the use of images for visual communication. Computers, Environment and Urban Systems, 29(3), 255-273. https://doi.org/10.1016/j.compenvurbsys.2004.05.002
Nudo, R. J. P. (2007). Postinfarct cortical plasticity and behavioral recovery. Stroke, 38, 840-845. https://doi.org/10.1161/01.STR.0000 247943.12887.d2
O’Neill, S. (2022). Defining a visual metonym: A hauntological study of polar bear imagery in climate communication. Transactions of the Institute of British Geographers, 47, 1104-1119. https://doi.org/10.1111/tran.12543
O’Neill, S. (2020). More than meets the eye: A longitudinal analysis of climate change imagery in the print media. Climatic Change 163, 9-26. https://doi.org/10.1007/s10584-019-02504-8
O’Neill, S. (2017). Engaging with climate change imagery. Oxford Research Encyclopedia of Climate Science. https://doi.org/10.1093/acrefore/9780190228620.013.371
O’Neill, S. y Hulme, M. (2009). An iconic approach for representing climate change. Global Environmental Change, 19(4), 402-410. https://doi.org/10.1016/j.gloenvcha.2009.07.004
Paré M. y Munoz, D. (2001). Expression of a recentering bias in saccade regulation by superior colliculus neurons. Experimental Brain Research, 137(3-4), 354-368. https://doi.org/10.1007/s002210000647
Pew Research Center (s.f.). Climate Change Concern Quiz. https://www.pewresearch.org/global/quiz/climate-change-concern-quiz/
Plutchik, R. (2001). The nature of emotions. American Scientist, 89(4), 344-350. https://doi.org/10.1511/2001.28.344
Powell, J. (2019). Scientists reach 100% consensus on anthropogenic global warming. Bulletin of Science, Technology & Society, 37(4), 183-184. https://doi.org/10.1177/0270467619886266
Rahmstorf, S. (2004). The climate sceptics weather catastrophes and climate change. Is there still hope for us. PG Verlag.
Ren, D., Wang, P., Qiao, H. y Zheng, S. (2013). A biologically inspired model of emotion eliciting from visual stimuli. Neurocomputing: An International Journal, 121, 328-336. https://doi.org/10.1177/0270467619886266
Richards, D. y Jacobson, E. (2022). How real is too real? User-testing the effects of realism as a risk communication strategy in sea level rise visualizations. Technical Communication Quarterly, 31(2), 190-206. https://doi.org/10.1080/10572252.2021.1986135
Ritter, M. (2020). Science says: How risky is that virus? Your mind may mislead. Associated Press, 5 de marzo. https://apnews.com/
Schneider, W. y Shiffrin, R. (1977). Controlled and automatic human information processing: I. detection, search, and attention. Psychological Review, 84(1), 1-66. https://doi.org/10.1037/0033-295X.84.1.1
Slovic, P. (2010a). The psychology of risk. Saúde E Sociedade, 19(4), 731-747. https://doi.org/10.1590/S0104-12902010000400002
Slovic, P. (2010b). Introduction and overview. En Slovic, P. (ed.), The feeling of risk: New perspectives on risk perception (pp. XIX-XXVII). Earthscan.
Sprague, T., Saproo, S. y Serences, J. (2015). Visual attention mitigates information loss in small- and large-scale neural codes. Trends in Cognitive Sciences, 19(4), 215-226. https://doi.org/10.1590/S0104-12902010000400002
Sutton, J. y Fischer, L. (2021). Understanding visual risk communication messages: An analysis of visual attention allocation and think-aloud responses to tornado graphics. Weather, Climate, and Society, 13(1), 173-188. https://doi.org/10.1175/WCAS-D-20-0042.1
Tatler, B. (2007). The central fixation bias in scene viewing: Selecting an optimal viewing position independently of motor biases and image feature distributions. Journal of Vision, 7(14), 1-17. https://doi.org/10.1167/7.14.4
Taub, E. y Uswatte, G. (2006). Constraint-induced movement therapy: Answers and questions after two decades of research. Neuro Rehabilitation, 21, 93-95. https://doi.org/10.3233/NRE-2006-21201
Watson, D., Clark, L. y Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063-1070. https://doi.org/10.1037//0022-3514.54.6.1063
Wilson, B. (2008). Neuropsychological rehabilitation. Annual Review of Clinical Psychology, 4, 141-162. https://doi.org/10.1146/annurev.clinpsy.4.022007.141212
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Hilda Paola Muñoz-Pico, Bienvenido León Anguiano
This work is licensed under a Creative Commons Attribution 4.0 International License.
1. Proposed Policy for Journals That Offer Open Access
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
