This investigation explored the relationships between individuals’ self-images and their interactions with their digital music collections via the commercially predominant program iTunes. Sixty-nine university students completed an internet-based Musical Self-Images Questionnaire (MSIQ) along with a series of questions concerning their iTunes collections. The majority of participants were highly engaged with music, regardless of their varied musical backgrounds. Factor analysis of the MSIQ data revealed two distinct self-image groups, which we label as ‘musical practitioner’ (linking ‘overall musician’, ‘performer’, ‘composer’, ‘teacher’, and ‘listener’) and ‘music consumer’ (linking ‘listener’, ‘fan’, and ‘technology user’). Participants used an average of seven attributes to categorize their music, and most consistently used one in particular to sort their collections. Those who rated themselves as higher level performers and fans used the playlist function (which involves compiling sequences of selected tracks) more often than those with lower self-ratings on those scales.
Krause, A.E., & North, A.C. (2012). Everyday listening experiences.
Utilizing the Experience Sampling Method, this investigation aimed to update our understanding of everyday listening in situ. Self-reports regarding where, when, and how music was experienced, as well as ratings concerning affect before and after exposure to music and the perceived effects of what was heard were gathered over one week. Responding to two text messages sent at random times between 8:00 and 23:00 daily, 370 participants completed online responses concerning their experience with any music heard within a two-hour period prior to receiving each text message. Results from the 177 participants who completed at least 12 of 14 entries demonstrated that music was heard on 46.31% of occasions overall. While heard throughout the day and more often in private than public spaces, detailed analyses revealed significant patterns based on time, location, device, selection method, mood, ratings of choice and attention, and the perceived effects of what was heard. Most importantly, the results suggest that it is the level of control that a person has over the auditory situation which greatly interacts with the other variables to influence how he or she will hear the music as well as how it is perceived. In contrast to North, Hargreaves, and Hargreaves (2004) proposition that the value of music has decreased in light of technological advancement, the current findings imply that with the greater control technology affords, the value has instead increased, when we consider individuals as actively consuming (thereby using) music rather than simply as passive listeners.
Krause, A.E., North, A.C., & Hewitt, L.Y. (2013). Listening devices and selection methods involved in everyday listening.
Digitization is changing the ways we consume music. The present two studies explored music listening in everyday life. In both, participants completed a questionnaire addressing demographics, technology use, and psychological constructs, such as identity, personality, and innovativeness. Study 1 focused on music-listening devices, and investigated whether technological and/or psychological variables could predict possession of a music technology identity, differences in the advantages perceived endemic to their preferred listening device, and whether differing devices were associated with music having different perceived consequences. The results indicate existence of a one-dimensional identity based on music technology and that psychological variables, such as innovativeness and self-efficacy, can predict whether individuals have such an identity. Moreover, while psychological variables predicted whether individuals considered ‘familiarized’ advantages important to listening devices, preferring ‘progressive’ advantages was predicted by technological behaviors. Additionally, differences in identity and the preference for different advantages were evident on the basis of an individual’s preferred listening device. Study 2 examined whether technology usage and/or psychological variables were related to individuals’ tendency to select their music in three ways (specific choice, playlists, and shuffle). The findings support those of the first study in terms of identity and also demonstrated that a different pattern of variables predicted playlist listening from listening to music on shuffle. Moreover, certain types of playlists were more commonly created and those with a more present-focused time perspective were likely to employ playlists. This research indicates that in order to understand how people interact with music in everyday life it is insufficient to merely map the demographic characteristics of the individuals concerned or to know how much time people spend with different music listening devices. Rather, a further consideration of psychological factors was able to add significantly to our understanding of how participants accessed their music.