| Grant number: | 23/03052-3 |
| Support Opportunities: | Scholarships abroad - Research |
| Start date: | January 01, 2024 |
| End date: | June 30, 2024 |
| Field of knowledge: | Linguistics, Literature and Arts - Arts - Music |
| Principal Investigator: | Graziela Bortz |
| Grantee: | Graziela Bortz |
| Host Investigator: | Massimo Grassi |
| Host Institution: | Instituto de Artes (IA). Universidade Estadual Paulista (UNESP). Campus de São Paulo. São Paulo , SP, Brazil |
| Institution abroad: | Università degli Studi di Padova, Italy |
Abstract The advantage of musicians over non-musicians in cognitive abilities and executive functions has been the subject of scrutiny in recent decades and, despite behavioral research, with neural correlates, pointing to such an advantage in some measures, such as short-term memory, working memory, inhibitory control, attention and social skills, there is still controversy in this regard. The main criticisms concern the uniformity of the investigated populations, being mainly the result of research with middle-class populations, from countries in global North and eminently white. In addition, a good part of the research was carried out with small samples, with little inferential power of causal effect. This study will be incorporated into a multicenter project in which 12 other units in other countries will participate, and it intends to gather sample data from at least 600 participants, 42 of which (21 musicians and 21 non-musicians) from Brazil. Data collection will begin in Brazil in 2023 and will continue, in 2024, at the project's host institution, Università degli Studi di Padova, in the Department of General Psychology. The Raven scales (Rosseti et al., 2009), BFI-2 (Zhang et al., 2022), WAIS-4 (Wechsler, 1955), Four-factor (Hollingshead, 1975), Mini-Proms (Zentner & Strauss, 2017), Gold-MSI (Lima et al., 2018; Müllensiefen et al., 2014), eBMRQ (Cardona et al., 2022), auditory n-back, and other customized scales. Pearson correlations will be calculated for variables separately for musicians and non-musicians. Three multilevel regression models will be calculated separately for each memory task. As predictors, interaction between groups and vocabulary GOLD-MSI, Raven, WAIS-IV, n-back, BFI-2, eBMRQ, socioeconomic status, age and years of schooling will be included. Using a model comparison approach, the best prediction model for each memory result will be selected. (AU) | |
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