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artículo
Gender inequality and cultural values in explaining gender differences in positive and negative emotions: A comparison of 24 countries during the COVID-19 pandemic
Publicado por
Wollast, Robin, Lüders, Adrian, Nugier, Armelle, Guimond, Serge, Phillips, Joseph B., Sutton, Robbie M., Douglas, Karen M., Sengupta, Nikhil K., Lemay, Edward P., Zand, Somayeh, Van Lissa, Caspar J., Bélanger, Jocelyn J., Abakoumkin, Georgios, Khaiyom, Jamilah Hanum Abdul, Agostini, Maximilian, Ahmedi, Vjollca, Almenara, Carlos A., Atta, Mohsin, Bagci, Sabahat C., Bernardo, Allan B.I., Choi, Hoon Seok, Cristea, Mioara, Danyliuk, Ivan, Enea, Violeta, Fisher, Alexandra N., Gómez, Angel, Greiff, Samuel, Gützkow, Ben, Hamaidia, Ali, Han, Qing, Hudiyana, Joevarian, Jeronimus, Bertus F., Jiang, Ding Yu, Jovanović, Veljko, Kende, Anna, Keng, Shian Ling, Koc, Yasin, Kovyazina, Kamila, Kreienkamp, Jannis, Kurapov, Anton, Lantos, Nora Anna, Jaya Lesmana, Cokorda Bagus, Malik, Najma I., Martinez, Anton P., McCabe, Kira O., Milla, Mirra N., Molinario, Erica, Moyano, Manuel, Muhammad, Hayat, Mula, Silvana, Myroniuk, Solomiia, Nisa, Claudia, Nyúl, Boglárka, O’Keefe, Paul A., Osuna, Jose Javier Olivas, Osin, Evgeny N., Park, Joonha, Pierro, Antonio, Rees, Jonas, Reitsema, Anne Margit, Rullo, Marika, Ryan, Michelle K., Samekin, Adil, Schumpe, Birga M., Selim, Heyla A., Stanton, Michael V., Tseliou, Eleftheria, vanDellen, Michelle, Vázquez, Alexandra, Weaving, Morgan, Yahiiaiev, Illia, Yeung, Victoria W.L., Zheng, Bang, Zúñiga, Claudia, Leander, N. Pontus
Publicado 2025 Enlace
The coronavirus pandemic posed a major challenge to mental health. Existing evidence shows that COVID-19 is related to poor emotional well-being, particularly among women. However, most work on the subject uses single-country samples, limiting the ability to generalize the disparity or explain it as a function of societal variables. The present study investigates the expression of positive and negative emotions during the pandemic as a function of gender and across 24 countries (N = 49,637). Strong gender differences emerged across countries, with women reporting more negative emotions (anxious, depressed, nervous, exhausted) and less positive emotions (calm, content, relaxed, energetic) than men. The gender gap in positive emotions was significantly wider in countries higher in individualism and narrower in countries higher in power distance. For instance, differences in emotions were l...
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2
artículo
Gender inequality and cultural values in explaining gender differences in positive and negative emotions: A comparison of 24 countries during the COVID-19 pandemic
Publicado por
Wollast, Robin, Lüders, Adrian, Nugier, Armelle, Guimond, Serge, Phillips, Joseph B., Sutton, Robbie M., Douglas, Karen M., Sengupta, Nikhil K., Lemay, Edward P., Zand, Somayeh, van Lissa, Caspar J., Bélanger, Jocelyn J., Abakoumkin, Georgios, Khaiyom, Jamilah Hanum Abdul, Agostini, Maximilian, Ahmedi, Vjollca, Almenara, Carlos A., Atta, Mohsin, Bagci, Sabahat C., Bernardo, Allan B. I., Choi, Hoon-Seok, Cristea, Mioara, Danyliuk, Ivan, Enea, Violeta, Fisher, Alexandra N., Gómez, Angel, Greiff, Samuel, Gützkow, Ben, Hamaidia, Ali, Han, Qing, Hudiyana, Joevarian, Jeronimus, Bertus F., Jiang, Ding-Yu, Jovanović, Veljko, Kende, Anna, Keng, Shian-Ling, Koc, Yasin, Kovyazina, Kamila, Kreienkamp, Jannis, Kurapov, Anton, Lantos, Nora Anna, Jaya Lesmana, Cokorda Bagus, Malik, Najma I., Martinez, Anton P., McCabe, Kira O., Milla, Mirra N., Molinario, Erica, Moyano, Manuel, Muhammad, Hayat, Mula, Silvana, Myroniuk, Solomiia, Nisa, Claudia, Nyúl, Boglárka, O’Keefe, Paul A., Osuna, Jose Javier Olivas, Osin, Evgeny N., Park, Joonha, Pierro, Antonio, Rees, Jonas, Reitsema, Anne Margit, Rullo, Marika, Ryan, Michelle K., Samekin, Adil, Schumpe, Birga M., Selim, Heyla A., Stanton, Michael V., Tseliou, Eleftheria, vanDellen, Michelle, Vázquez, Alexandra, Weaving, Morgan, Yahiiaiev, Illia, Yeung, Victoria W. L., Zheng, Bang, Zúñiga, Claudia, Leander, N. Pontus
Publicado 2025 Enlace
The coronavirus pandemic posed a major challenge to mental health. Existing evidence shows that COVID-19 is related to poor emotional well-being, particularly among women. However, most work on the subject uses single-country samples, limiting the ability to generalize the disparity or explain it as a function of societal variables. The present study investigates the expression of positive and negative emotions during the pandemic as a function of gender and across 24 countries (N = 49,637). Strong gender differences emerged across countries, with women reporting more negative emotions (anxious, depressed, nervous, exhausted) and less positive emotions (calm, content, relaxed, energetic) than men. The gender gap in positive emotions was significantly wider in countries higher in individualism and narrower in countries higher in power distance. For instance, differences in emotions we...
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3
artículo
Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic
Publicado por
van Lissa, Caspar J., Stroebe, Wolfgang, vanDellen, Michelle R., Leander, N. Pontus, Agostini, Maximilian, Draws, Tim, Grygoryshyn, Andrii, Gützgow, Ben, Kreienkamp, Jannis, Vetter, Clara S., Abakoumkin, Georgios, Abdul Khaiyom, Jamilah Hanum, Ahmedi, Vjolica, Akkas, Handan, Almenara, Carlos A., Atta, Mohsin, Bagci, Sabahat Cigdem, Basel, Sima, Kida, Edona Berisha, Bernardo, Allan B.I., Buttrick, Nicholas R., Chobthamkit, Phatthanakit, Choi, Hoon Seok, Cristea, Mioara, Csaba, Sára, Damnjanović, Kaja, Danyliuk, Ivan, Dash, Arobindu, Di Santo, Daniela, Douglas, Karen M., Enea, Violeta, Faller, Daiane Gracieli, Fitzsimons, Gavan J., Gheorghiu, Alexandra, Gómez, Ángel, Hamaidia, Ali, Han, Qing, Helmy, Mai, Hudiyana, Joevarian, Jeronimus, Bertus F., Jiang, Ding Yu, Jovanović, Veljko, Kamenov, Željka, Kende, Anna, Keng, Shian Ling, Thanh Kieu, Tra Thi, Koc, Yasin, Kovyazina, Kamila, Kozytska, Inna, Krause, Joshua, Kruglanksi, Arie W., Kurapov, Anton, Kutlaca, Maja, Lantos, Nóra Anna, Lemay, Edward P., Jaya Lesmana, Cokorda Bagus, Louis, Winnifred R., Lueders, Adrian, Malik, Najma Iqbal, Martinez, Anton P., McCabe, Kira O., Mehulić, Jasmina, Milla, Mirra Noor, Mohammed, Idris, Molinario, Erica, Moyano, Manuel, Muhammad, Hayat, Mula, Silvana, Muluk, Hamdi, Myroniuk, Solomiia, Najafi, Reza, Nisa, Claudia F., Nyúl, Boglárka, O'Keefe, Paul A., Olivas Osuna, Jose Javier, Osin, Evgeny N., Park, Joonha, Pica, Gennaro, Pierro, Antonio, Rees, Jonas H., Reitsema, Anne Margit, Resta, Elena, Rullo, Marika, Ryan, Michelle K., Samekin, Adil, Santtila, Pekka, Sasin, Edyta M., Schumpe, Birga M., Selim, Heyla A., Stanton, Michael Vicente, Sultana, Samiah, Sutton, Robbie M., Tseliou, Eleftheria, Utsugi, Akira, Anne van Breen, Jolien, van Veen, Kees, Vázquez, Alexandra, Wollast, Robin, Wai-Lan Yeung, Victoria, Zand, Somayeh
Publicado 2022 Enlace
Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual-level injunctive norms. Illustrating how ...
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