The relaxation effects of stimulative and sedative music on mathematics anxiety: a perception to physiology model

Gan, Samuel Ken-En, Lim, Keane Ming-Jie, and Haw, Yu-Xuan (2016) The relaxation effects of stimulative and sedative music on mathematics anxiety: a perception to physiology model. Psychology of Music, 44 (4). pp. 730-741.

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Abstract

Previous research on music and mathematics anxiety has relied primarily on self-reports without biological measurements. To address whether these parameters were correlated, we included blood pressure physiological measures, the State-Trait Anxiety Inventory (STAI) and the Mathematics Anxiety Rating Scale (MARS) in our study. One hundred and five psychology undergraduates were assigned to sedative, stimulative and "no music" conditions while completing Cambridge GCE O Level mathematical questions. Anxiety was measured pre-, during and posttest. Results showed that MARS was positively correlated with STAI, but not with the physiological measures. A 3 x 3 mixed ANOVA showed differences between the sedative and no music condition for the measures of STAI and MARS, but not for the physiological measures. Further analyses using t-tests found sedative music to elicit a pronounced decrease in systolic blood pressure and the stimulative music to have minimal effect. To explain these findings and the discrepancy with previous studies, we propose a Perception-to-Physiology model for the effect of music in anxiety.

Item ID: 43608
Item Type: Article (Research - C1)
ISSN: 1741-3087
Keywords: mathematics anxiety, music, physiological, relaxation, self-reports
Funders: James Cook University (JCU), Bioinformatics Institute, Singapore, Agency for Science, Technology and Research, Singapore
Date Deposited: 18 Apr 2016 22:22
FoR Codes: 52 PSYCHOLOGY > 5201 Applied and developmental psychology > 520102 Educational psychology @ 70%
36 CREATIVE ARTS AND WRITING > 3603 Music > 360301 Music cognition @ 30%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970117 Expanding Knowledge in Psychology and Cognitive Sciences @ 100%
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