How culturally unique are pandemic effects? Evaluating cultural similarities and differences in effects of age, biological sex, and political beliefs on COVID impacts

Despite being bio-epidemiological phenomena, the causes and effects of pandemics are culturally influenced in ways that go beyond national boundaries. However, they are often studied in isolated pockets, and this fact makes it difficult to parse the unique influence of specific cultural psychologies. To help fill in this gap, the present study applies existing cultural theories via linear mixed modeling to test the influence of unique cultural factors in a multi-national sample (that moves beyond Western nations) on the effects of age, biological sex, and political beliefs on pandemic outcomes that include adverse financial impacts, adverse resource impacts, adverse psychological impacts, and the health impacts of COVID. Our study spanned 19 nations (participant N = 14,133) and involved translations into 9 languages. Linear mixed models revealed similarities across cultures, with both young persons and women reporting worse outcomes from COVID across the multi-national sample. However, these effects were generally qualified by culture-specific variance, and overall more evidence emerged for effects unique to each culture than effects similar across cultures. Follow-up analyses suggested this cultural variability was consistent with models of pre-existing inequalities and socioecological stressors exacerbating the effects of the pandemic. Collectively, this evidence highlights the importance of developing culturally flexible models for understanding the cross-cultural nature of pandemic psychology beyond typical WEIRD approaches

The Experience of Stigma and Coping among Marginalized Students in Three South East Asian Countries: A Cross-Cultural Study

This study aims to 1) explore the experience of stigma across various marginalized student groups, including from indigenous and ethnic-minority groups, in three South-East Asian countries (the Philippines, Indonesia, and Malaysia); and 2) investigate how these groups coped with the experienced stigma. Data will be collected through interviews that purposive and snowball sampling methods will be used to contact potential participants who are: 1) aged 18 or older; 2) from a marginalized/indigenous group; 3) still active as a student; and 4) being a student for at least one year. Interviews will be transcribed and analyzed using content analysis - KJ Analysis developed by a Japanese ethnologist, Jiro Kawakita, in eight steps. After the completion of country-level analysis, the identified clusters between countries where both common as well as distinct themes relative to each research question/objective will be identified through cross-cultural and countries comparison