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Start Over Author "Apps, Matthew A. J." Publisher linkopings universitet, filosofiska fakulteten
6 results on '"Apps, Matthew A. J."'

1. Addressing climate change with behavioral science: A global intervention tournament in 63 countries

Author

Vlasceanu, Madalina, Doell, Kimberly C., Bak-Coleman, Joseph B., Todorova, Boryana, Berkebile-Weinberg, Michael M., Grayson, Samantha J., Patel, Yash, Goldwert, Danielle, Pei, Yifei, Chakroff, Alek, Pronizius, Ekaterina, van den Broek, Karlijn L., Vlasceanu, Denisa, Constantino, Sara, Morais, Michael J., Schumann, Philipp, Rathje, Steve, Fang, Ke, Aglioti, Salvatore Maria, Alfano, Mark, Alvarado-Yepez, Andy J., Andersen, Angélica, Anseel, Frederik, Apps, Matthew A. J., Asadli, Chillar, Awuor, Fonda Jane, Azevedo, Flavio, Basaglia, Piero, Bélanger, Jocelyn J., Berger, Sebastian, Bertin, Paul, Białek, Michał, Bialobrzeska, Olga, Blaya-Burgo, Michelle, Bleize, Daniëlle N. M., Bø, Simen, Boecker, Lea, Boggio, Paulo S., Borau, Sylvie, Bos, Björn, Bouguettaya, Ayoub, Brauer, Markus, Brick, Cameron, Brik, Tymofii, Briker, Roman, Brosch, Tobias, Buchel, Ondrej, Buonauro, Daniel, Butalia, Radhika, Carvacho, Héctor, Koppel, Lina, Västfjäll, Daniel, Tinghög, Gustav, Vlasceanu, Madalina, Doell, Kimberly C., Bak-Coleman, Joseph B., Todorova, Boryana, Berkebile-Weinberg, Michael M., Grayson, Samantha J., Patel, Yash, Goldwert, Danielle, Pei, Yifei, Chakroff, Alek, Pronizius, Ekaterina, van den Broek, Karlijn L., Vlasceanu, Denisa, Constantino, Sara, Morais, Michael J., Schumann, Philipp, Rathje, Steve, Fang, Ke, Aglioti, Salvatore Maria, Alfano, Mark, Alvarado-Yepez, Andy J., Andersen, Angélica, Anseel, Frederik, Apps, Matthew A. J., Asadli, Chillar, Awuor, Fonda Jane, Azevedo, Flavio, Basaglia, Piero, Bélanger, Jocelyn J., Berger, Sebastian, Bertin, Paul, Białek, Michał, Bialobrzeska, Olga, Blaya-Burgo, Michelle, Bleize, Daniëlle N. M., Bø, Simen, Boecker, Lea, Boggio, Paulo S., Borau, Sylvie, Bos, Björn, Bouguettaya, Ayoub, Brauer, Markus, Brick, Cameron, Brik, Tymofii, Briker, Roman, Brosch, Tobias, Buchel, Ondrej, Buonauro, Daniel, Butalia, Radhika, Carvacho, Héctor, Koppel, Lina, Västfjäll, Daniel, and Tinghög, Gustav

Abstract

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors., Funding Agencies|Google Jigsaw grant; Swiss National Science Foundation [P400PS_190997]; Dutch Research Council [7934]; John Templeton Foundation [61378]; National council for Scientific and technological development grant; Swiss Federal Office of energy through the energy, economy, and Society program; Christ church college Research centre grant [Si/502093- 01]; National Research Foundation of Korea [NRF- 2020S1A3A2A02097375]; Kieskompas-election compass; National Agency of Research and Development; National Doctoral Scholarship [24210087]; Dutch Science Foundation (NWO) [Vi.Veni.201S.075]; Netherlands Organization for Scientific Research (NWO) [453- 15- 005]; Foundation for Science and technology-Fct (Portuguese Ministry of Science, technology and higher education) [UidB/05380/2020]; Slovak Research and development Agency (APVV) [APVV- 21- 0114]; James Mcdonnell Foundation; Swedish Research council [2018- 01755]; Russian Federation Government [075- 15- 2021- 611]

Published
2024
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2. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Author

Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, Tinghög, Gustav, Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, and Tinghög, Gustav

Abstract

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Published
2022
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3. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Author

Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, Tinghög, Gustav, Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, and Tinghög, Gustav

Abstract

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Published
2022
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4. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Author

Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, Tinghög, Gustav, Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, and Tinghög, Gustav

Abstract

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Published
2022
Full Text
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5. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Author

Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, Tinghög, Gustav, Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, and Tinghög, Gustav

Abstract

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Published
2022
Full Text
View/download PDF

6. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Author

Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, Tinghög, Gustav, Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, Birtel, Michèle D, Schönegger, Philipp, Capraro, Valerio, Santamaría-García, Hernando, Yucel, Meltem, Ibanez, Agustin, Rathje, Steve, Wetter, Erik, Stanojević, Dragan, van Prooijen, Jan-Willem, Hesse, Eugenia, Elbaek, Christian T, Franc, Renata, Pavlović, Zoran, Mitkidis, Panagiotis, Cichocka, Aleksandra, Gelfand, Michele, Alfano, Mark, Ross, Robert M, Sjåstad, Hallgeir, Nezlek, John B, Cislak, Aleksandra, Lockwood, Patricia, Abts, Koen, Agadullina, Elena, Amodio, David M, Apps, Matthew A J, Aruta, John Jamir Benzon, Besharati, Sahba, Bor, Alexander, Choma, Becky, Cunningham, William, Ejaz, Waqas, Farmer, Harry, Findor, Andrej, Gjoneska, Biljana, Gualda, Estrella, Huynh, Toan L D, Imran, Mostak Ahamed, Israelashvili, Jacob, and Tinghög, Gustav

Abstract

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Published
2022
Full Text
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