Author ORCID Identifier

http://orcid.org/0000-0002-5030-0584

Year of Publication

2017

Degree Name

Master of Music (MM)

Document Type

Master's Thesis

College

Fine Arts

Department

Music

First Advisor

Dr. Olivia Yinger

Abstract

Lyric analysis is one of the most commonly used music therapy interventions with the mental health population, yet there is a gap in the research literature regarding song selection. The primary purpose of this study was to determine distinguishing linguistic characteristics of song lyrics most commonly used for lyric analysis with mental health consumers, as measured by LIWC2015 software. A secondary purpose was to provide an updated song list resource for music therapists and music therapy students working with the mental health population. The researcher emailed a survey to 6,757 board-certified music therapists, 316 of whom completed the survey. Respondents contributed 700 different songs that they deemed most effective for lyric analysis with mental health consumers. The researcher used the LIWC2015 software to analyze the 48 songs that were listed by five or more music therapists. Song lyrics contained linguistic indicators of self-focused attention, present-focused attention, poor social relationships, and high cognitive processing. Lyrics were written in an informal, personal, and authentic style. Some lyrics were more emotionally positive, while others were more emotionally negative. While results must be interpreted with caution, it may be helpful to consider linguistic elements when choosing songs for lyric analysis with mental health consumers.

Digital Object Identifier (DOI)

https://doi.org/10.13023/ETD.2017.180

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