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Your search keyword '"Atta, Mohsin"' showing total 2 results
Start Over Author "Atta, Mohsin" Publication Type Magazines
2 results on '"Atta, Mohsin"'

1. Prevalence of Bullying and Victimization among Sixth Graders with Reference to Gender, Socio-economic Status and Type of Schools

Author

Shujja, Sultan, Atta, Mohsin, and Shujjat, Jawwad Muhammad

Abstract

AbstractCurrent study was aimed to find overall prevalence of bullying, victimization and fighting behavior among 836 sixth graders (M = 12, SD= 1.20) and specifically in context of socio-economic status, type of schools and, gender in Pakistan. Data were collected from 16 private and public schools using Illinois Bullying Scale (Urdu translation) along with demographic form. Findings revealed 19.6% - 24.1% prevalence among sixth graders generally and 20.9% - 21.8% among children of low socio-economic status and, 22.7% - 23.6% among average socio-economic status specifically. Furthermore, prevalence among private and public school children ranged from 20.4% - 23.8% and 19.1% - 24.9% respectively. Children of public schools were found more involved in bullying, fighting and victimizing others as compared to private school children. Gender-wise prevalence has been found as 22%- 24.9% in boys and 22% in girls. Boys were engaged in more bullying, victimization and fighting than girls.

Published
2014
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2. Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Author

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, Žeželj, Iris Lav, Zheng, Bang, Zick, Andreas, Zúñiga, Claudia, and Bélanger, Jocelyn J.

Abstract

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 data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically derived predictors were relatively unimportant.

Published
2022
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