Social representation of “music” in young adults: a cross-cultural study

Vinaya Manchaiah*, Fei Zhao, Stephen Widén, Jasmin Auzenne, Eldré W. Beukes, Tayebeh Ahmadi, David Tomé, Deepthi Mahadeva, Rajalakshmi Krishna, Per Germundsson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)
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Abstract

Objective: This study was aimed to explore perceptions of and reactions to music in young adults (18–25 years) using the theory of social representations (TSR). Design: The study used a cross-sectional survey design and included participants from India, Iran, Portugal, USA and UK. Data were analysed using various qualitative and quantitative methods. Study sample: The study sample included 534 young adults. Results: The Chi-square analysis showed significant differences between the countries regarding the informants’ perception of music. The most positive connotations about music were found in the responses obtained from Iranian participants (82.2%), followed by Portuguese participants (80.6%), while the most negative connotations about music were found in the responses obtained from Indian participants (18.2%), followed by Iranian participants (7.3%). The participants’ responses fell into 19 main categories based on their meaning; however, not all categories were found in all five countries. The co-occurrence analysis results generally indicate that the category “positive emotions or actions” was the most frequent category occurring in all five countries. Conclusions: The results indicate that music is generally considered to bring positive emotions for people within these societies, although a small percentage of responses indicate some negative consequences of music.

Original languageEnglish
Pages (from-to)24-32
Number of pages9
JournalInternational Journal of Audiology
Volume56
Issue number1
DOIs
Publication statusPublished - 9 Sept 2016

Keywords

  • Music listening
  • attitude
  • cross-culture
  • hearing loss
  • public health hazard
  • social representation
  • text mining

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