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The Role of Location in Everyday Experiences of Music
Amanda E. Krause, Adrian C. North, and Lauren Y. HewittCurtin University
Mehrabian and Russell’s (1974) Pleasure–Arousal–Dominance model states that apropensity to approach/avoid an environment can be conceptualized in terms of thepleasure and arousal it elicits and one’s degree of dominance therein. Using theExperience Sampling Method, 177 individuals provided responses concerning Mehra-bian and Russell’s model throughout 1 wk regarding music experiences that occurredin their daily life (including how the music was heard and how their responses relatedto the listening location). Results indicate that the time of day and day of week arerelated to where music is experienced, and that the consequences of what was heard arerelated to both time and location. Although music was experienced more often inprivate locations than in public overall, interesting patterns of music experiences thatoccurred in public locations demonstrate in detail how music listening varies bylocation. Specifically, portable devices were associated with positive responses, whichcontrasted sharply with the responses to music broadcasted publicly in public settings.Participants’ ratings of choice, liking, and arousal demonstrated the importance ofconsidering choice as an indication of dominance, such that music usage is consistentwith Mehrabian and Russell’s model, and has functions that vary according to thespecific characteristics of the situation.
Keywords: music, experience sampling method, everyday life, location, choice
In everyday life, music listening occurs in avariety of locations and contexts (e.g., listeningas a part of a social gathering or through head-phones alone), and for many different reasons(Watson & Mandryk, 2012). With mobile de-vices, personal computers, and the Internet, op-portunities for interacting with music havenever before been so varied (North, Hargreaves,& Hargreaves, 2004; O’Hara & Brown, 2006),and have allowed people to expand the places,times, and ways in which they experience music(Heye & Lamont, 2010; Juslin, Liljeström,Västfjäll, Barradas, & Silva, 2008; Sloboda,Lamont, & Greasley, 2009). However, one lim-itation of the existing research concerns therelative lack of detail describing the currentcontext of everyday listening in light of techno-
logical developments, as this has clear implica-tions for the theoretical explanations developed.
Most listening encounters still occur at home(Juslin et al., 2008; Komulainen, Karukka, &Hakkila, 2010; North et al., 2004; Watson &Mandryk, 2012); prior research foundthat �50% (North et al., 2004)—or �64%(Greasley & Lamont, 2011)—of music epi-sodes occurred at home. However, people inwestern societies experience a great deal ofmusic throughout the day (Greasley & Lamont,2011), including in a variety of commercialenvironments (North et al., 2004). In short, peo-ple encounter music in a range of everydaycontexts, and potentially experience music dif-ferently as a consequence. In turn, any theoret-ical account of musical experience must accountfor these varying contexts in which they occur.
Therefore, the purpose of this research is toconsider the role of location in everyday musiclistening. Although previous research (North etal., 2004) broadly considered where listeningtakes place, the rise of mobile and Internet-connected devices demands further investiga-tion of this topic. The data used in the presentstudy were collected at the same time as thatpresented in two recent publications (Krause,
This article was published Online First October 20, 2014.Amanda E. Krause, Adrian C. North, and Lauren Y.
Hewitt, School of Psychology and Speech Pathology, CurtinUniversity.
Correspondence concerning this article should be ad-dressed to Amanda E. Krause, School of Psychology andSpeech Pathology, Curtin University, GPO Box U1987,Perth, WA 6845. E-mail: [email protected]
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Psychology of Popular Media Culture © 2014 American Psychological Association2016, Vol. 5, No. 3, 232–257 2160-4134/16/$12.00 http://dx.doi.org/10.1037/ppm0000059
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North, & Hewitt, 2013, 2015), which detail thedevices and selection behaviors involved in ev-eryday listening, but which did not address lo-cation. Therefore, the aim of the present articleis to explicitly consider the role of location ineveryday listening. Further, in doing so it con-siders Mehrabian and Russell’s model as a po-tential theoretical framework for understandingeveryday listening: the model provides a com-prehensive conceptualization of the location(see previous nonmusical research—Hines &Mehrabian, 1979; Yani-de-Soriano & Foxall,2006) in terms of pleasure, arousal, and domi-nance. Previous work has shown that these threefactors (to varying degrees and with varyingdegrees of specificity) are relevant to under-standing the role of the immediate situation inindividuals’ attitudes and behavior.
Background
Where does listening take place? One possi-ble broad categorization dichotomizes listeninglocations as essentially private (e.g., at home) orpublic spaces (e.g., at a shop or restaurant).Prior research has indicated that individualshave more choice regarding their listening athome, in private (North et al., 2004), but gen-erally encounter unchosen music while out inpublic (Sloboda, 2005). Moreover, in public,unchosen music was met with ambivalence oreven disliked (Sloboda, 2005; Sloboda &O’Neill, 2001). Many criticize the perceivedintrusiveness and unwanted nature of music ex-perienced in public (Skånland, 2011), includingactive campaigns against music used in storesand public places (such as the United King-dom’s Pipedown) for instance. We might ex-pect, therefore, that music heard at home or inprivate spaces would be liked more and givenmore attention than that encountered in publicspaces, as people would likely feel more dom-inant/in control.
However, in present-day western society, thepublic versus private distinction may be sim-plistic. Even when in public, new mobile tech-nology affords listeners the opportunity to cre-ate their own “auditory bubbles” viaheadphones and mobile devices (Bull, 2007). Infact, the majority of participants in Komulainenet al.’s (2010) study indicated listening to musicin more than five locations on a weekly basis.Locations included at home and others’ houses,
but also in public settings such as at school,walking and on public transportation, in cars, atthe gym, and while shopping (Komulainen etal., 2010). For some users, mobile listeningdevices may act as “digital Sherpas” (Bull,2007)1 that provide a companion as individualsgo about their daily routines and traverse dif-ferent settings. In public, individuals can usemp3 players as resources to create (and retreatto) a private environment, exerting control byselecting music to listen to (Skånland, 2011). Inthis manner, mobile devices provide an oppor-tunity for people to exercise choice over theirauditory environment even in public settings,such that mobile devices may offer listeners analtered sense of dominance over their auditoryenvironment. How might new listening technol-ogies relate to where the listening takes place?
New technologies mean that, in addition toconsidering whether the physical location is inpublic or private, it is important to consider thelevel of choice and control a person has over themusic he or she is exposed to in those situations.We anticipate that—in contrast to previous re-search—high levels of choice and control mightbe observed in public locations, depending onthe device by which the music in question isaccessed in those settings: it is necessary toconsider how the music is encountered, withregard to devices and selection behaviors, in ourunderstanding of listening episodes in differentlocations.
Mehrabian and Russell’sPleasure–Arousal–Dominance Model
Mehrabian and Russell’s (1974—see alsoAndersson, Kristensson, Wästlund, & Gustafs-son, 2012; Hines & Mehrabian, 1979) theory ofenvironmental psychology asserts that people’sinteractions and interpretation of their contex-tual surroundings result from variations in threefactors. The first two are pleasure and arousal.Pleasure–displeasure is a feeling state such asfeeling good or happy; and the arousal factorrefers to the extent to which one feels stimu-
1 One definition of “Sherpa” is a person who guidesmountain climbers as well as helps carry gear. With the term“digital Sherpas,” Bull (2007) refers to a mobile listeningdevice that accompanies a listener and mediates their expe-riences: it can function as a constant guide to users as theytraverse their day through different locations.
233MUSIC AND LOCATION
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lated, alert, or active in an environment. How-ever, the third factor, dominance (the extent towhich one controls one’s environment), hasbeen subject to relatively little examination.This is particularly pertinent in the light of thematerial above describing how modern technol-ogy directly influences the amount of controlone exerts over one’s own auditory environ-ment. Indeed, applying this theory of environ-mental psychology to understanding music lis-tening behaviors, pleasure, and arousal in amusic listening episode can be conceptualizedas one’s degree of preference (or liking) for themusic, and how arousing one finds the music.Mehrabian and Russell were less precise in theirdefinition of dominance, and, in fact, the inclu-sion of dominance in the model has been de-bated with its role downplayed in previous re-search (Yani-de-Soriano & Foxall, 2006).Dominance has tended to be defined using theadjective pair “dominance–submissiveness,”and operationalized as one’s “degree of controlover a situation versus degree of being con-trolled by a situation” (Hines & Mehrabian,1979, p. 224). One unfortunate consequence ofthis definition and operationalization is that, se-mantically, the term “submissiveness” simplydoes not make sense in a musical context: re-search participants would likely be confused ifinvited to consider the extent to which the musicin a situation is controlling them. Consequently,the present research adopted a more suitabledefinition of dominance, and one that does lenditself to music listening behaviors, which opera-tionalizes the concept in terms of having controlover one’s contextualized music listening.
Indeed, music has often been considered interms of pleasure and arousal. Musical prefer-ences vary according to the situation, reflectingthe emotional connotations of the situations:North and Hargreaves (1996a) found that peo-ple prefer music that has the same emotionalconnotations as the situation in which listeningoccurs, so that, for example, people in calmsituations prefer calming music. In retail set-tings, consumers respond to environmentalcues, including music: preference for music, forinstance, has a significant effect on consumers’cognitive and emotional evaluations, which, inturn, affect approach and affiliation behaviors(Sweeney & Wyber, 2002). North and Har-greaves (1996b) focused on music preference inparticular, demonstrating a positive correlation
between liking the music and liking the atmo-sphere of a cafeteria and the likelihood of ap-proaching an information stall. Moreover, mu-sical preference relates to arousal goals in asituation: individuals preferred “high-arousalmusic” for aerobic exercise activity but “low-arousal music” during guided relaxation. How-ever, when stating preferences after relaxing orexercising, participants’ music selections sug-gested attempts at moderating their arousal lev-els (North & Hargreaves, 2000), indicating thatdifferent arousal states may be considered ap-propriate for different situations (Hargreaves &North, 2010). An individual’s opportunity touse arousal-based strategies in everyday musiclistening in situ is of course growing, as digitaltechnology makes music more portable.
In contrast, previous research on music hastended to ignore dominance and, similarly, re-search on the Mehrabian and Russell (1974)model has debated the importance of this factorpartly because research was able to obtain im-pressive findings using just the pleasure andarousal dimensions (Desmet, 2010; Donovan,Rossiter, Marcoolyn, & Nesdale, 1994; Mattila& Wirtz, 2001). More recent work, however,has concluded that the three-dimensional model(including dominance) is superior to the two-dimensional model (Yani-de-Soriano & Foxall,2006). Although situations that provoke plea-sure and dominance are most preferred (Meh-rabian, Wihardja, & Ljunggren, 1997), peopleare not always in control of the music theyencounter. However, as a consequence of digitaltechnology and the myriad of ways we encoun-ter music, dominance (conceptualized as controlrelated to the music) may be a key component tounderstanding everyday listening.
In addition to the theoretically driven argu-ments derived from the Mehrabian and Russell(1974) model, there are also more data-drivengrounds for suspecting that control may be im-portant in everyday music listening. A body ofpsychological research has demonstrated thatcontrol (and even the perception or illusion ofcontrol) over aspects of one’s life mediates as-pects of health and well-being, and reactions topain and stress in particular (Lachman &Weaver, 1998; Lee, Ford, & Gramotnev, 2009;Mitchell, MacDonald, & Knussen, 2008), suchthat we anticipate that having a greater degreeof choice in what is heard will likely correspondto positive reactions. For example, a person’s
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own, preferred music has been found to signif-icantly increase his or her perceived controlover painful stimuli and reduce anxiety (Mitch-ell & MacDonald, 2006; Mitchell et al., 2008).In this way, we expect a similar pattern offindings concerning dominance in the context ofmusic listening to that identified by research inother contexts concerning the Mehrabian andRussell model: locations conducive to peopleexerting control/choice over their listening(dominance) will be met with positive re-sponses, such as greater preference for the mu-sic, and positive mood and consequence re-sponses.
Present Study
The Experience Sampling Method (see Csik-szentmihalyi & Lefevre, 1989), a methodologythat asks participants to respond to prompts inreal time, is well suited to explore the role oflocation in everyday music listening. It offers away to examine individuals’ subjective real-time musical experiences while maintaininghigh ecological validity (Sloboda, O’Neill, &Ivaldi, 2001). Given the literature reviewed, wedeveloped the following five research questionsand hypotheses. Numbers 1–3 concern specificdetails of how music listening takes place, andset the context for numbers 4 and 5, which makepredictions based on Mehrabian and Russell’smodel—
1: Where does everyday listening take place?North et al. (2004) reported that 50.1% of thetotal listening occurrences took place within thehome, while 17.9% occurred in overtly publicplaces (such as a restaurant, gym, shoppingmall, etc.). We expect that the majority of lis-tening experiences will still take place at home.However, we also expect that the percentage oflistening episodes occurring in places outsidethe home will be greater, leading to a lowerpercentage of listening episodes occurring athome than indicated by previous research.
2: Does the time of day or week relate to thelocation of everyday music listening? North etal. (2004) found that a greater percentage oflistening incidences occurred later in the eve-ning and at the weekend. To determine this theycalculated the proportion of episodes in whichmusic could be heard, and did so separately foreach hour of the day and for each day of theweek. The percentage of occasions on which
music could be heard ranged from 20% to 46%between 7:00 and 18:59, whereas the percent-ages ranged from 51% to 69% between 19:00and 22:59, and the overall percentage for week-days was 36% whereas the corresponding figurefor weekends was 46%. We expect that al-though listening may still take place to a greaterdegree at these times (namely in the eveningand at the weekend), the percentage correspond-ing to hearing music during daytime hours willbe greater than previously reported due to mo-bile and computer listening devices allowingpeople to listen to music in the locations inwhich they find themselves in the daytime, suchas the workplace.
3: How is music heard (e.g., device and se-lection behaviors) in private and public loca-tions? By acknowledging that this is partiallydetermined by what is available in a location,we anticipate that the means by which music isheard will be more varied in private locationsthan in public. Further, we expect that listeningin public locations will occur via mobile devicesin addition to broadcasted recorded music that isout of one’s personal control. Regarding selec-tion behaviors, we anticipate that selection be-haviors that rely more on individualized input(such as choosing a particular song or creating apersonal playlist) will take place in private lo-cations as an expression of dominance over thelistening situation by the individual.
4: How do ratings of pleasure, arousal, anddominance relate to music listening in differinglocations? Although past research has focusedon pleasantness and arousal, we expect thatdominance may also relate to responses to mu-sic in everyday listening locations. We expectthat people will express higher ratings of choicein private versus public locations, and that thesewill also be associated with higher ratings ofliking for the music. However, regardless oflocation, high choice ratings will likely be madewhen listening via mobile devices. We alsoexpect that there will be variations betweenlocations in the arousing qualities of the musicexperienced (North & Hargreaves, 1996c,2000). In particular, we anticipate high arousalratings to be associated with the music experi-enced in situations in which individuals delib-erately seek a high level of arousal (e.g., whileat the gym); similarly, listening episodes thatoccur at work may indicate the selection ofmusic of low arousal-evoking properties, in an
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apparent attempt to use music to induce calm, orminimize distraction.
5: Does location relate to the perceived con-sequences of hearing music? Given the findingsof previous Experience Sampling Method re-search concerning music (Greasley & Lamont,2011; Juslin et al., 2008; North et al., 2004), wemight expect that motivations for listening aresituation dependent and apparently reflect anintention of using music to help achieve abroader goal. For instance, North et al. (2004)found that a reason such as “it helped me con-centrate” was selected particularly in situationswhere participants were doing intellectual tasks,while listening as a “habit” occurred duringroutine activities, such as doing housework andeating. As these motivations for listening tomusic were situation dependent (North et al.,2004), we expect differences in the conse-quences of music experienced in different loca-tions based on interpretations of how the musicassisted or hindered a person’s broader objec-tives in that place.
Method
Participants
In total, 177 individuals residing in theUnited Kingdom completed the weeklongstudy. Recruitment included posters, informa-tion on the Internet, and emails to students andalumni at a university in Scotland. The sampleincluded 101 females (57.06%) and was aged17–75 years (M: 32.70, Mdn: 28, SD: 14.61).The majority of the sample identified their legalnationality as United Kingdom/Ireland(85.88%), and all were required to use a UnitedKingdom mobile telephone to participate (andso were legal residents of the country). Abouthalf of the sample was employed (51.41%),while 41.24% were students, 4.52% were re-tired, 2.26% were stay at home carers, and0.56% were unemployed.
Design and Procedure
Data presented here were collected at thesame time as that reported in (Krause et al.,2013, 2015). To begin, participants completed ashort online background questionnaire reportingtheir age, sex, musical background, level ofengagement with music, and contact details.
Participants wrote open-ended responses re-garding their musical background and educa-tion, which were then rated by three judges asrepresenting low, moderate, and high musicalbackground/experience (North & Hargreaves,1995). “Low” level classification pertained tothose participants with no to little experience,“moderate” referred to playing an instrumentrecreationally or to Grade 5 within the U.K.examination structure, and “high” reflectedplaying an instrument proficiently (beyond U.K.examination structure Grade 5) and those whowere professional musicians, music teachers, orhaving studied music at the university level. Asdefined, 49.7%, 38.4%, and 11.9% participantswere allocated to low, moderate, and high mu-sical experience groupings, respectively. Theintraclass correlation coefficient for the threeraters was .89.
Two questions probed music engagement:participants indicated how many hours they lis-ten to music on an average day and rated howimportant they consider music to be on a 7-pointscale (1 � not at all, 7 � extremely). In return,participants were given a unique identificationnumber and detailed information about the re-sponse procedure.
For seven days, participants received two textmessages sent to their personal mobile tele-phones daily—one between 8:00 and 15:29 andone between 15:30 and 23:00—prompting themto complete a response entry online as soon asthey could safely do so. An online random dayand time value generator (random.org) was usedto select times for the text messages within eachtime period, and a free Internet service (esemes.co.uk) was used to send the texts. An onlineresponse form was used following a pilot testtrialing both paper and online formats to maxi-mize completion rates.
Each entry required participants to enter theirunique identification number, the date and timethey received the text message, and the time thatthey completed the entry. If participants had notheard music in the 2-hr period prior to receivingthe text message, they simply noted this. If theyhad heard music, they then responded to a seriesof questions regarding the most recent listeningexperience.
Participants reported where they were froma list of options namely at home, at work, at afriend’s house, at the gym, driving a car, in acar, public transportation, walking, restaurant,
236 KRAUSE, NORTH, AND HEWITT
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pub/club, concert, shopping, religious worship,in class/university lecture, and other. In additionto this, individuals indicated the device throughwhich the music was played (i.e., mobile mp3player, mobile telephone, mobile CD player,computer own, computer stream, computercloud, mp3 stereo device, CD stereo device,radio, TV, live music in a public place, andrecorded music broadcasted in public) and howthe music was selected (i.e., specific song, spe-cific artist, specific album, personal premadeplaylist, a premade playlist made by someoneelse, random/shuffle, live performance, radio,watched TV, Web site streaming, “I did nothave any control,” “someone I was with chose,”and other).
Participants responded to four questionsabout the music using 7-point scales (1 � none/not at all to 7 � total/very much), including“How much choice did you have in what youheard,” “How much attention were you payingto the music,” “How much did you like whatyou heard,” and “How arousing was the musicyou heard?” Lastly, individuals responded to 12statements adapted from North et al. (2004)concerning the consequences of experiencingmusic: a principal components analysis of rat-ings in response to these statements (reported in[reference removed]) showed that the conse-quences could be grouped into three factors,namely purposive listening, actively engagedlistening, and validation-seeking listening. Forexample, “learning about the music” and “en-joying the music” were characteristic of activelyengaged listening, while helping concentrationand motivation were characteristic of purposivelistening, and use to “help a person look good”was characteristic of validation-seeking listen-ing. (Note that the entire questionnaire appearsin the Appendix.)
Results
Data Analysis
The data presented concern the episodes forwhich participants indicated that music washeard. To account for the fact that individualparticipants completed multiple responses, a hi-erarchical structure whereby episodes werenested within participants was used when per-forming generalized linear mixed method
(GLMM) analyses (� � .008, unless otherwisenoted).
Overall Location Frequencies
The first research question considered whereeveryday listening takes place. Participants se-lected where each music experience took placefrom a list of 15 options. Three locations (shop-ping, religious worship, university lecture/class)received fewer than 15 responses, so were re-moved from further analyses. Participants se-lected “other” for only 4.3% of their musicexperiences, indicating that the list of choicesadequately described nearly all listening events.Consistent with North et al.’s (2004) findings,the home was the most common location forpeople to experience music. Overall frequenciesrevealed that music was heard next most oftenwhen driving a car, and while at work (seeTable 1).
The location options were also grouped intotwo categories: private and public spaces(henceforth considered as “location type”). Athome, at a friend’s house, driving a car, and ina car comprised the private space category, andthe remainder (excluding “other”) comprisedthe public space category. Overall, 73.25% of
Table 1Overall Frequencies of Reported Locations
Location Frequency PercentValid
percenta
At home 462 42.0 44.0Driving a car 177 16.1 16.9At work 113 10.3 10.8Public transportation 70 6.4 6.7In a car 63 5.7 6.0Other 47 4.3 4.5At a friend’s house 32 2.9 3.1Walking 23 2.1 2.2At the gym 22 2.0 2.1Restaurant 21 1.9 2.0Pub/Club 19 1.7 1.8Total 1049 95.4 100.0Removed:
Missing 17 1.5Shopping 14 1.3Concert 7 0.6Religious worship 7 0.6In class/University lecture 6 0.5Total 1100 100
a “Valid percent” expresses the percentage of responsesconsidered in the analyses.
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the music experiences occurred in private spac-es. Although listening incidents in public set-tings were less frequent, their greater preva-lence when compared with North et al.’s 2004findings may be indicative of the growing use ofportable digital technology.
When and Where Music Listening Happens
To address the second research question, aseries of analyses were performed that consid-ered time of day, day of week, location type,and the specific locations.
First, a GLMM analysis considered if partic-ipant background characteristics influencedwhether music was experienced in public orprivate locations. Age, sex, music importancerating, average daily listening amount (hours),and music education level were entered as pre-dictor variables (see Table 2). Age and theaverage listening amount were both significant,such that younger participants were more likelyto experience music in public locations thanolder participants and those who reported lis-tening to more hours of music on average werealso more likely to encounter music in publiclocations compared with those who spend lesshours listening.
A GLMM analysis tested for an associationbetween time of day (namely, 8:00–8:59, 9:00–16:59, 17:00–20:59, and 21:00–23:59) and lo-cation type (public vs. private space; F(3,998) � 13.77, p � .001, �p
2 � .040; see Table3). The time of day intervals were based on atypical day in that 8:00–8:59 might be consid-ered “before work,” 9:00–16:59 as during workhours, 17:00–20:59 as after work hours, and21:00–23:59 as late night.
During each period of the day, the incidencepercentage was higher for private spaces thanfor public spaces. However, additionally, signif-
icant pairwise comparisons indicated that 8:00–8:59, 17:00–20:59, and 21:00–23:59 were allsignificantly more likely to involve private lo-cations than public when compared with 9:00–16:59. Moreover, music heard between 21:00–23:59 was significantly more likely to be heardin private than that between 17:00–20:59. Thispattern is not surprising due to the likelihood ofbeing at home at the early and later time peri-ods. In fact, being at home was the most com-mon location in which to experience musicacross every time period, and individuals weremost likely to hear music in a pub/club between17:00–20:59 and 21:00–23:59.
A GLMM analysis revealed an associationbetween the part of the week (weekday vs.weekend) and location type (F(1, 1000) � 15.21, p � .001, �p
2 � .015; see Table 3). Musicwas heard in private spaces significantly moreoften at the weekend than on weekdays. AGLMM analysis between part of the week andspecific locations also revealed significant con-trasts as displayed in Table 4 (F(10, 1038) �4.36, p � .001, �p
2 � .013). Specifically, hearingmusic at work and at the gym was more likelyto occur on weekdays than weekends in com-parison with being in a car, at a restaurant, andat home. Hearing music at a friend’s houseoccurred more often on the weekends comparedwith eight of the other locations. Moreover,listening at home occurred to a greater extent atthe weekend than during the week comparedwith driving or using public transportation.
Device Usage by Location
The third research question concerned theinteraction between location and device use. AGLMM analysis demonstrated a significant as-
Table 2Participant Background Variables Predicting Private Versus PublicMusic Episodes
Predictor F �p2
Age F(1, 996) � 12.61, p � .001 .012Sex F(1, 996) � 0.10, p � .755 .000Music importance rating F(1, 996) � 0.79, p � .373 .001Average daily listening amount (hr) F(1, 996) � 5.55, p � .019 .006Music education level F(1, 996) � 0.00, p � .990 .000
Note. N � 1002.
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Table 3Pairwise Contrasts Pertaining to the GLMM Analyses Considering Private Versus PublicMusic Experiences
Predictor variable Pairwise contrast t 95% CI �2
Time of day Pre work (8:00–8:59)–Work day (9:00–16:59) 4.63��� [0.12, 0.29] .021Pre work (8:00–8:59)–After work (17:00–20:59) 1.95 [0.00, 0.18] .004Pre work (8:00–8:59)–Late night (21:00–23:59) �0.44 [�0.11, 0.07] .000Work day (9:00–16:59)–After work (17:00–20:59) �3.29�� [�0.18, �0.05] .011Work day (9:00–16:59)–Late night (21:00–23:59) �6.56��� [�0.29, �0.16] .041After work (17:00–20:59)–Late night (21:00–23:59) �3.21�� [�0.18, �0.04] .010
Part of week Weekday–Weekend �4.39��� [�0.20, �0.08] .019Device Mobile mp3 player–Mobile telephone �0.57 [�0.36, 0.20] .000
Mobile mp3 player–Mobile CD player �4.21��� [�0.78, �0.28] .017Mobile mp3 player–Computer—own �9.05��� [�0.76, �0.49] .076Mobile mp3 player–Computer—stream �3.56��� [�0.60, �0.18] .013Mobile mp3 player–Computer—cloud �3.02�� [�0.70, �0.15] .009Mobile mp3 player–Stereo—mp3 device �7.23��� [�0.73, �0.42] .050Mobile mp3 player–Stereo—CD �9.43��� [�0.75, �0.49] .082Mobile mp3 player–Radio �8.85��� [�0.69, �0.44] .073Mobile mp3 player–TV �7.38��� [�0.71, �0.41] .052Mobile mp3 player–In public—live �1.04 [�0.63, 0.19] .001Mobile mp3 player–In public—recorded 4.36��� [0.16, 0.43] .019Mobile telephone–Mobile CD player �2.59� [�0.79, �0.11] .007Mobile telephone–Computer—own �4.04��� [�0.80, �0.28] .016Mobile telephone–Computer—stream �1.78 [�0.65, 0.03] .003Mobile telephone–Computer—cloud �1.88 [�0.70, 0.02] .004Mobile telephone–Stereo—mp3 device �3.41�� [�0.77, �0.21] .012Mobile telephone–Stereo—CD �4.07��� [�0.80, �0.28] .016Mobile telephone–Radio �3.59��� [�0.75, �0.22] .013Mobile telephone–TV �3.18�� [�0.78, �0.18] .010Mobile telephone–In public—live �0.55 [�0.62, 0.35] .000Mobile telephone–In public—recorded 2.79�� [0.11, 0.64] .008Mobile CD player–Computer—own �0.80 [0.31, 0.13] .001Mobile CD player–Computer—stream 0.94 [�0.15, 0.44] .001Mobile CD player–Computer—cloud 0.67 [�0.21, 0.42] .000Mobile CD player–Stereo—mp3 device �0.32 [�0.28, 0.20] .000Mobile CD player–Stereo—CD �0.80 [�0.32, 0.13] .001Mobile CD player–Radio �0.29 [�0.25, 0.19] .000Mobile CD player–TV �0.27 [�0.26, 0.20] .000Mobile CD player–In public—live 1.35 [�0.14, 0.77] .002Mobile CD player–In public—recorded 7.23��� [0.60, 1.05] .050Computer—own–Computer—stream 2.43 [0.04, 0.42] .006Computer—own–Computer—cloud 1.47 [�0.07, 0.46] .002Computer—own–Stereo—mp3 device 0.81 [�0.07, 0.17] .001Computer—own–Stereo—CD �0.05 [�0.08, 0.08] .000Computer—own–Radio 1.48 [�0.02, 0.14] .002Computer—own–TV 1.14 [�0.04, 0.16] .001Computer—own–In public—live 1.95 [0.00, 0.81] .004Computer—own–In public—recorded 21.95��� [0.84, 1.00] .326Computer—stream–Computer—cloud �0.23 [�0.34, 0.27] .000Computer—stream–Stereo—mp3 device �1.61 [�0.40, 0.04] .003Computer—stream–Stereo—CD �2.42� [�0.42, �0.04] .006Computer—stream–Radio �1.86 [�0.36, 0.01] .003Computer—stream–TV �1.72 [�0.37, 0.02] .003Computer—stream–In public—live 0.75 [�0.28, 0.62] .001Computer—stream–In public—recorded 6.94��� [0.49, 0.88] .046Computer—cloud–Stereo—mp3 device �1.02 [�0.43, 0.14] .001Computer—cloud–Stereo—CD �1.50 [�0.46, 0.06] .002
(table continues)
239MUSIC AND LOCATION
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Table 3 (continued)
Predictor variable Pairwise contrast t 95% CI �2
Computer—cloud–Radio �1.05 [�0.40, 0.12] .001Computer—cloud–TV �1.00 [�0.41, 0.13] .001Computer—cloud–In public—live 0.90 [�0.25, 0.66] .001Computer—cloud–In public—recorded 5.36��� [0.46, 0.99] .028Stereo—mp3 device–Stereo—CD �0.83 [�0.18, 0.07] .001Stereo—mp3 device–Radio 0.12 [�0.12, 0.13] .000Stereo—mp3 device–TV 0.12 [�0.13, 0.15] .000Stereo—mp3 device–In public—live 1.66 [�0.06, 0.77] .003Stereo—mp3 device–In public—recorded 13.29��� [0.74, 1.00] .150Stereo—CD–Radio 1.61 [�0.01, 0.13] .003Stereo—CD–TV 1.27 [�0.03, 0.16] .002Stereo—CD–In public—live 1.99� [0.01, 0.81] .004Stereo—CD–In public—recorded 22.51��� [0.84, 1.00] .337Radio–TV 0.02 [�0.10, 0.10] .000Radio–In public—live 1.64 [�0.07, 0.76] .003Radio–In public—recorded 20.75��� [0.78, 0.94] .301TV–In public—live 1.64 [�0.07, 0.76] .003TV–In public—recorded 13.77��� [0.74, 0.98] .160In public—live–In public—recorded 2.49� [0.11, 0.92] .006
Selection method I did not have control–Someone I was with chose �4.99��� [�0.59, �0.26] .024I did not have control–Specific artist �2.77�� [�0.44, �0.07] .008I did not have control–Specific album �4.56��� [�0.53, �0.21] .020I did not have control–Specific song �3.32�� [�0.58, �0.15] .011I did not have control–It was performed live at the
time�1.30 [�0.62, 0.13] .002
I did not have control–Random/shuffle �2.14� [�0.37, �0.02] .005I did not have control–Personal premade playlist �1.78 [�0.39, 0.02] .003I did not have control–Premade playlist made by
someone else�0.42 [�0.35, 0.23] .000
I did not have control–Listened to the radio �6.20��� [�0.57, �0.29] .037I did not have control–Watched TV �6.72��� [�0.65, �0.35] .043I did not have control–Web site streaming �4.12��� [�0.59, �0.21] .017I did not have control–Other �5.99��� [�0.67, �0.34] .035Someone I was with chose–Specific artist 1.91 [�0.01, 0.34] .004Someone I was with chose–Specific album 0.64 [�0.10, 0.20] .000Someone I was with chose–Specific song 0.57 [�0.14, 0.26] .000Someone I was with chose–It was performed live at
the time0.90 [�0.21, 0.55] .001
Someone I was with chose–Random/shuffle 2.65�� [0.06, 0.40] .007Someone I was with chose–Personal premade playlist 2.21� [0.03, 0.44] .005Someone I was with chose–Premade playlist made by
someone else2.50� [0.08, 0.64] .006
Someone I was with chose–Listened to the radio �0.13 [�0.14, 0.12] .000Someone I was with chose–Watched TV �1.19 [�0.21, 0.05] .001Someone I was with chose–Web site streaming 0.26 [�0.14, 0.19] .000Someone I was with chose–Other �1.03 [�0.23, 0.07] .001Specific artist–Specific album �1.85 [�0.24, 0.01] .003Specific artist–Specific song �1.01 [�0.32, 0.10] .001Specific artist–It was performed live at the time 0.05 [�0.36, 0.38] .000Specific artist–Random/shuffle 0.77 [�0.10, 0.23] .001Specific artist–Personal premade playlist 0.66 [�0.14, 0.27] .000Specific artist–Premade playlist made by someone else 1.35 [�0.09, 0.48] .002Specific artist–Listened to the radio �2.52� [�0.31, �0.04] .006Specific artist–Watched TV �3.54��� [�0.38, �0.11] .012Specific artist–Web site streaming �1.43 [�0.34, 0.05] .002Specific artist–Other �3.02��� [�0.41, �0.09] .009Specific album–Specific song 0.11 [�0.17, 0.19] .000Specific album–It was performed live at the time 0.71 [�0.22, 0.48] .001
240 KRAUSE, NORTH, AND HEWITT
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Table 3 (continued)
Predictor variable Pairwise contrast t 95% CI �2
Specific album–Random/shuffle 2.64�� [0.05, 0.32] .007Specific album–Personal premade playlist 2.02� [0.01, 0.37] .004Specific album–Premade playlist made by someone
else2.30� [0.01, 0.37] .005
Specific album–Listened to the radio �1.16 [0.05, 0.58] .001Specific album–Watched TV �2.54� [�0.23, �0.03] .006Specific album–Web site streaming �0.30 [�0.20, 0.14] .000Specific album–Other �1.92 [�0.26, 0.00] .004Specific song–It was performed live at the time 0.62 [�0.25, 0.49] .000Specific song–Random/shuffle 1.66 [�0.03, 0.38] .003Specific song–Personal premade playlist 1.45 [�0.06, 0.42] .002Specific song–Premade playlist made by someone else 1.99� [0.00, 0.60] .004Specific song–Listened to the radio �0.74 [�0.24, 0.11] .001Specific song–Watched TV �1.61 [�0.30, 0.03] .003Specific song–Web site streaming �0.33 [�0.25, 0.18] .000Specific song–Other �1.41 [�0.33, 0.05] .002It was performed live at the time–Random/shuffle 0.31 [�0.30, 0.41] .000It was performed live at the time–Personal premade
playlist0.30 [�0.33, 0.45] .000
It was performed live at the time–Premade playlistmade by someone else
0.84 [�0.25, 0.62] .001
It was performed live at the time–Listened to the radio �1.02 [�0.54, 0.17] .001It was performed live at the time–Watched TV �1.43 [�0.60, 0.09] .002It was performed live at the time–Web site streaming �0.80 [�0.53, 0.22] .001It was performed live at the time–Other �1.30 [�0.64, 0.13] .002Random/shuffle–Personal premade playlist 0.03 [�0.20, 0.21] .000Random/shuffle––Premade playlist made by someone
else0.91 [�0.15, 0.41] .001
Random/shuffle–Listened to the radio �3.49�� [�0.37, �0.11] .012Random/shuffle–Watched TV �4.46��� [�0.45, �0.17] .020Random/shuffle–Web site streaming �2.34� [�0.38, �0.03] .005Random/shuffle–Other �3.89��� [�0.47, �0.15] .015Personal premade playlist–Premade playlist made by
someone else0.84 [�0.17, 0.42] .001
Personal premade playlist–Listened to the radio �2.85�� [�0.41, �0.08] .008Personal premade playlist–Watched TV �3.55��� [�0.49, �0.14] .012Personal premade playlist–Web site streaming �1.83 [�0.44, 0.02] .003Personal premade playlist–Other �3.46�� [�0.49, �0.14] .012Premade playlist made by someone else–Listened to
the radio�2.80�� [�0.63, �0.11] .008
Premade playlist made by someone else–Watched TV �3.35�� [�0.70, �0.81] .011Premade playlist made by someone else–Web site
streaming�2.34� [�0.62, �0.06] .005
Premade playlist made by someone else–Other �3.38�� [�0.69, �0.19] .011Listened to the radio–Watched TV �1.75 [�0.15, 0.01] .003Listened to the radio–Web site streaming 0.40 [�0.12, 0.18] .000Listened to the radio–Other �1.23 [�0.19, 0.04] .002Watched TV–Web site streaming 1.28 [�0.05, 0.26] .002Watched TV–Other �0.02 [�0.10, 0.10] .000Web site streaming–Other �1.14 [�0.28, 0.07] .001
Note. The reference category was “Public” locations.� p � .05. �� p � .01. ��� p � .001.
241MUSIC AND LOCATION
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Table 4Pairwise Contrasts Pertaining to the GLMM Analysis Considering the Location of Music Experiences onWeekdays Versus Weekends (N � 1049)
Location pair t 95% CI �2
At home–At a friend’s house 2.72�� [0.07, 0.46] .007At home–At work �4.93��� [�0.25, �0.11] .023At home–At the gym �2.75�� [�0.30, �0.05] .007At home–Driving a car �2.82�� [�0.16, �0.03] .008At home–In a car 1.26 [�0.05, 0.21] .002At home–Public transportation �2.95�� [�0.23, �0.05] .008At home–Walking �0.69 [�0.19, 0.09] .000At home–Restaurant 0.92 [�0.13, 0.36] .001At home–Pub/Club �0.64 [�0.23, 0.12] .000At home–Other �1.24 [�0.19, 0.04] .001At a friend’s house–At work �4.34��� [�0.64, �0.24] .018At a friend’s house–At the gym �3.99��� [�0.66, �0.22] .015At a friend’s house–Driving a car �3.60��� [�0.56, �0.17] .012At a friend’s house–In a car �1.51 [�0.42, 0.05] .002At a friend’s house–Public transportation �3.80��� [�0.61, �0.20] .014At a friend’s house–Walking �2.67�� [�0.54, �0.08] .007At a friend’s house–Restaurant �0.86 [�0.50, 0.19] .001At a friend’s house–Pub/Club �2.53� [�0.57, �0.07] .006At a friend’s house–Other �3.22�� [�0.55, �0.13] .010At work–At the gym 0.04 [�0.12, 0.12] .000At work–Driving a car 2.06� [0.00, 0.16] .004At work–In a car 3.64��� [0.12, 0.40] .013At work–Public transportation 0.82 [�0.06, 0.14] .001At work–Walking 1.77 [�0.01, 0.27] .003At work–Restaurant 2.37� [0.05, 0.54] .005At work–Pub/Club 1.34 [�0.06, 0.30] .002At work–Other 1.61 [�0.02, 0.23] .002At the gym–Driving a car 1.21 [�0.05, 0.21] .001At the gym–In a car 2.98�� [0.09, 0.43] .008At the gym–Public transportation 0.64 [�0.08, 0.15] .000At the gym–Walking 0.13 [�0.06, 0.31] .000At the gym–Restaurant 2.15� [0.03, 0.56] .004At the gym–Pub/Club 1.14 [�0.09, 0.33] .001At the gym–Other 1.17 [�0.07, 0.27] .001Driving a car–In a car 2.63�� [0.05, 0.31] .007Driving a car–Public transportation �0.84 [�0.14, 0.05] .001Driving a car–Walking 0.66 [�0.09, 0.19] .000Driving a car–Restaurant 1.73 [�0.03, 0.45] .003Driving a car–Pub/Club 0.45 [�0.14, 0.22] .000Driving a car–Other 0.36 [�0.10, 0.14] .000In a car–Public transportation �2.93�� [�0.37, �0.07] .008In a car–Walking �1.38 [�0.32, 0.06] .002In a car–Restaurant 0.25 [�0.22, 0.28] .000In a car–Pub/Club �1.31 [�0.35, 0.07] .002In a car–Other �2.07� [�0.31, �0.01] .004Public transportation–Walking 1.04 [�0.08, 0.26] .001Public transportation–Restaurant 1.90 [�0.01, 0.51] .003Public transportation–Pub/Club 0.86 [�0.11, 0.27] .001Public transportation–Other 0.86 [�0.08, 0.21] .001Walking–Restaurant 1.18 [�0.11, 0.44] .001Walking–Pub/Club �0.06 [�0.22, 0.21] .000Walking–Other �0.30 [�0.19, 0.14] .000Restaurant–Pub/Club �1.12 [�0.47, 0.13] .001Restaurant–Other �1.41 [�0.45, 0.07] .002Pub/Club–Other �0.19 [�0.22, 0.18] .000
� p � .05. �� p � .01. ��� p � .001.
242 KRAUSE, NORTH, AND HEWITT
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sociation between location type and the devicefrom which the music was heard (F(11, 980) �10.63, p � .001, �p
2 � .108; Table 3). Signifi-cant pairwise contrasts illustrate that recordedmusic broadcasted publicly was significantlymore likely to be heard in public locations com-pared with every other device. Mobile mp3 de-vices were significantly more likely involved inpublic locations than mobile CD players, com-puters (personal, streaming, and cloud collec-tions), stereo devices (both mp3 and CD), theradio, and TV. Similarly mobile telephoneswere significantly more often associated withpublic experiences than mobile CD players, per-sonal computer collections, stereo (mp3 andCD), radio, and TV. Additional differences ex-isted for computer devices: a personal collectionon a computer was a device more likely used inprivate than a computer streaming device and acomputer streaming device more likely used inpublic than a stereo CD device. Stereo mp3devices were significantly more private thanmusic performed live as well.
The frequencies of music experiences associ-ated with various devices across the specificlocations (see Table 5) reveal that the radio,computer, and TV were the three predominantdevices in the home. While driving and in thecar, music experienced via stereo CD was thesecond most frequent device behind the radio.In contrast, mobile telephones and mp3 playerstogether accounted for �86.9% of all the de-vices used on public transportation and whenwalking. At the gym, mp3 player usage wasmost popular as well. Most of the music heardin a restaurant and while in a pub/club wasrecorded music broadcasted publicly. Lastlywhile at work, the radio accounted for 40.0% ofmusical experiences, with the remaining per-centage shared across the computer, mobile, andstereo devices. The greater prevalence of mo-bile devices (as opposed to exposure to recordedmusic) in public settings indicates a shift in ourability to shape our listening outside of privatespaces (such as the home). No longer do weonly encounter prerecorded music from loud-speakers while in public: we are far more likelyto encounter music in public via mobile devices.
Selection Behavior by Location
A GLMM analysis examined the method bywhich people selected music in terms of loca-
tion type (private vs. public). The results dem-onstrated a series of significant pairwise con-trasts between selection methods by locationtype (F(12, 970) � 6.37, p � .001, �p
2 � .073;see Table 3). As might be expected, not havingany control occurred more often in public thanprivate when compared with most of the otherselection behaviors (including someone I waswith chose, specific artist specific album, spe-cific song, random/shuffle, personal playlist, ra-dio, TV, and Web site streaming). In contrast,someone I was with chose and specific albumswere both selection behaviors more associatedwith private experiences than public experi-ences compared with random/shuffle, and bothplaylist types. Additionally, radio and TV weresignificantly more likely to occur in private thanrandom/shuffle, playlists made by other people,and personal playlists (Web site streaming alsowas significantly more likely to occur in privatecompared with random/shuffle and playlistsmade by someone else). Moreover, TV wasmore often private than specific albums andspecific songs more often private than playlistsby someone else.
Cross-tabulating the selection method fre-quencies across the specific locations indicatedthe existence of more detailed patterns (see Ta-ble 5). Concerning specifically when “at afriend’s house,” both someone I was with choseand I did not have control were relatively com-mon selection methods. When traveling by car,the radio was most common device and selec-tion method indicated, although a differencebetween driver and passenger regarding select-ing the music was evident: choosing a specificalbum was a more common selection methodwhen driving, whereas someone else chose oc-curred to a greater degree when participantsindicated that they were passengers. These re-sults suggest that drivers were afforded controlover music selection as well as driving itself.Moreover, the high incidence of selecting spe-cific albums corresponds with the high preva-lence of stereo CD device usage in this setting.
Public settings again highlight striking con-trasts in how music is played and selected basedon location. Shuffling was popular on publictransportation and when walking, but selectinga specific artist was cited most frequently onpublic transportation, while listening to a per-sonal playlist was more common while walking.Similarly personal playlists and random/shuffle
243MUSIC AND LOCATION
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Tab
le5
Rep
orte
dD
evic
ean
dSe
lect
ion
Met
hod
Fre
quen
cies
byA
llL
ocat
ions
Var
iabl
eIt
emA
tho
me
At
afr
iend
’sho
use
At
wor
kA
tth
egy
mD
rivi
nga
car
Ina
car
Publ
ictr
ansp
orta
tion
Wal
king
Res
taur
ant
Pub/
club
Oth
erT
otal
Dev
ice
Mob
ilem
p323
19
923
451
170
09
146
Mob
ileph
one
132
64
40
183
00
252
Mob
ileC
D7
10
13
20
10
01
16C
ompu
ter—
own
9810
70
00
10
00
011
6C
ompu
ter—
stre
am37
318
00
00
00
04
62C
ompu
ter—
clou
d15
38
00
00
01
01
28St
ereo
—m
p3de
vice
232
100
116
00
00
153
Ster
eo—
CD
511
12
338
00
11
310
1R
adio
965
441
102
420
01
12
294
TV
911
51
00
00
15
410
8In
publ
ic—
live
42
11
00
02
02
1426
Inpu
blic
—re
cord
ed1
01
30
00
017
95
36T
otal
459
3111
022
176
6270
2321
1846
1038
Sele
ctio
nm
etho
dI
did
not
have
any
cont
rol
444
164
61
12
1815
912
0So
meo
neI
was
with
chos
e27
1110
17
80
00
04
68Sp
ecifi
car
tist
382
40
53
203
00
277
Spec
ific
albu
m65
110
132
512
20
05
133
Spec
ific
song
171
40
34
50
00
337
Itw
aspe
rfor
med
live
atth
etim
e5
11
11
00
00
38
20
Ran
dom
/shu
ffle
491
135
131
168
00
210
8Pr
emad
epl
aylis
t—yo
urow
n36
13
610
110
61
03
77
Prem
ade
play
list—
mad
eby
som
eone
else
90
52
41
02
20
227
Lis
tene
dto
the
radi
o81
337
194
374
00
00
257
Wat
ched
TV
541
30
10
00
00
261
Web
site
stre
amin
g19
05
00
00
00
02
26O
ther
83
00
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10
00
519
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al45
229
111
2117
762
6923
2118
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30
244 KRAUSE, NORTH, AND HEWITT
Thi
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ent
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were most common at the gym, where the mostused device was a mobile mp3 player.
Choice, Attention, Liking, and Arousal
Research question 4 considered how ratingsof pleasure, arousal, and dominance relate tomusic listening in differing locations. To ad-dress this question, four separate GLMM anal-yses (� � .013) were performed to examinewhether the 11 locations were associated withdifferences in respondents’ ratings of choice,attention, liking, or arousal (see Tables 6 and 7).
Regarding choice ratings (F(10, 1031) � 21.27, p � .001, �p
2 � .171), significant deviationcontrasts indicated that at home, driving a car,and public transportation were three locationsassociated with significantly higher choice rat-ings than the overall mean. In contrast, a res-taurant and pub/club were two locations forwhich choice ratings were significantly lowerthan the overall mean.
The analysis of attention ratings was alsosignificant (F(10, 1029) � 8.71, p � .001, �p
2 �.078). Significant deviation contrasts indicatethat at home, public transportation, and walkingwere associated with significantly higher thanoverall mean attention ratings, while at workand at a restaurant were associated with ratingsthat were significantly lower than the overallmean attention rating.
Significant deviation contrasts demonstratedthat the liking ratings for at home and publictransportation were associated with signifi-cantly higher liking ratings compared with theoverall mean and at a restaurant was associatedwith significantly lower liking ratings comparedwith the overall mean (overall analysis: F(10,1031) � 9.87, p � .001, �p
2 � .087).Regarding arousal ratings (F(10, 1028) �
6.86, p � .001, �p2 � .063), significant deviation
contrasts demonstrated that those associatedwith being at the gym were significantly higherthan the overall arousal mean, while arousalratings for restaurant and at work were signifi-cantly lower than the overall mean.
Consequences
Three GLMM analyses were performed toexamine the final research question, namelywhether time and location interacted to affectthe perceived consequences of a given musicexperience. The three factor scores concerning T
able
6E
stim
ated
Mea
ns,
Stan
dard
Err
ors,
and
95%
Con
fiden
ceIn
terv
als
ofth
eG
LM
MA
naly
ses
Con
cern
ing
Cho
ice,
Att
enti
on,
Lik
ing,
and
Aro
usal
Rat
ings
Loc
atio
n
Cho
ice
(N�
1042
)A
ttent
ion
(N�
1040
)L
ikin
g(N
�10
42)
Aro
usal
(N�
1039
)
MSE
95%
CI
MSE
95%
CI
MSE
95%
CI
MSE
95%
CI
At
hom
e4.
860.
16[4
.54,
5.18
]4.
540.
10[4
.35,
4.73
]5.
500.
08[5
.34,
5.66
]4.
400.
10[4
.21,
4.59
]A
ta
frie
nd’s
hous
e3.
380.
43[2
.54,
4.21
]4.
670.
25[4
.17,
5.16
]5.
640.
28[5
.09,
6.18
]4.
490.
31[3
.87,
5.10
]A
tw
ork
4.48
0.38
[3.7
4,5.
23]
3.63
0.19
[3.2
7,4.
00]
5.22
0.18
[4.8
7,5.
57]
4.01
0.20
[3.6
2,4.
40]
At
the
gym
4.40
0.61
[3.2
1,5.
59]
4.43
0.36
[3.7
1,5.
14]
5.38
0.34
[4.7
1,6.
04]
6.06
0.26
[5.5
5,6.
57]
Dri
ving
aca
r4.
840.
20[4
.45,
5.23
]4.
370.
13[4
.11,
4.63
]5.
470.
11[5
.26,
5.68
]4.
360.
16[4
.05,
4.66
]In
aca
r4.
400.
28[3
.86,
4.95
]4.
420.
20[4
.03,
4.81
]5.
100.
17[4
.77,
5.44
]4.
230.
20[3
.84,
4.62
]Pu
blic
tran
spor
tatio
n6.
170.
27[5
.65,
6.69
]5.
270.
20[4
.89,
5.65
]6.
170.
11[5
.96,
6.38
]4.
370.
20[3
.98,
4.76
]W
alki
ng5.
830.
53[4
.79,
6.87
]4.
920.
33[4
.28,
5.56
]5.
780.
30[5
.20,
6.37
]4.
830.
37[4
.11,
5.55
]R
esta
uran
t1.
070.
38[0
.33,
1.81
]2.
710.
28[2
.16,
3.25
]3.
820.
30[3
.23,
4.41
]2.
960.
30[2
.35,
3.57
]Pu
b/cl
ub1.
330.
41[0
.53,
2.13
]3.
700.
47[2
.79,
4.62
]4.
490.
43[3
.64,
5.34
]4.
880.
43[4
.04,
5.71
]O
ther
3.97
0.41
[3.1
7,4.
77]
4.77
0.30
[4.1
9,5.
35]
5.29
0.23
[4.8
4,5.
73]
4.65
0.29
[4.0
8,5.
21]
245MUSIC AND LOCATION
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sdo
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ent
isco
pyri
ghte
dby
the
Am
eric
anPs
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cal
Ass
ocia
tion
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the consequences of the music (namely activelyengaged, purposive, and validation-seeking lis-tening) were entered as the dependent variablesand location type (public vs. private), part of theweek (weekday vs. weekend), and time of day(1 � 8:00–8:59, 2 � 9:00–16:59, 3 � 17:00–20:59, and 4 � 21:00–23:59), as well as thepossible interactions were entered as predictorvariables (see Tables 8–10).
The part of week by location type interactionwas significant for purposive listening. Pairwisecomparisons (see Table 10) illustrate that pur-posive consequences experienced in publicspaces were significantly different dependent onwhether the episode occurred at a weekday orweekend. In particular, the purposive conse-quence was experienced more positively onweekdays as compared with weekends.
For actively engaged consequences, thesignificant location type by time of day inter-action demonstrated that individuals per-ceived the consequence differently when theindividual was in public depending on thetime of day (there were no significant differ-ences in private locations). Specifically, sig-nificant pairwise comparisons indicated thatthe actively engaged consequences were per-ceived more positively if the music is heardpublicly between 8:00 – 8:59 compared with9:00 –16:59 and 17:00 –20:59. Moreover, theactively engaged consequence was also expe-rienced more positively between 17:00 –20:59than between 9:00 –16:59 in public locations.Additionally, the part of week by time of dayinteraction was significant. On the weekends(but not weekdays), the perception of the ac-tively engaged consequence was dependenton the time of day. Specifically, from 8:00 –8:59, participants perceived the actively en-gaged consequence more positively in publicspaces as compared with 9:00 –16:59 and 17:00 –20:59 as well as for the music heard be-tween 17:00 –20:59 compared with 9:00 –16:59.
No interactions or main effects were signifi-cant with regard to validation-seeking listening.
The three GLMM analyses were then re-peated using the 11 specific locations as a pre-dictor rather than location types. No interactionswere significant, and only the location variablewas significant as a main effect for purposivelistening (see Tables 11 and 12). The motivatingaspect of music while at the gym is evident fromT
able
7D
evia
tion
Con
tras
tR
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tsF
rom
the
GL
MM
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lyse
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enti
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ings
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ice
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al
t95
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[1.6
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[0.6
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king
—m
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3.62
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[0.8
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00
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e.D
egre
esof
free
dom
(DF)
�10
42fo
rch
oice
and
likin
g;10
29fo
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tent
ion;
and
1028
for
arou
sal.
�p
�.0
5.��
p�
.01.
���
p�
.001
.
246 KRAUSE, NORTH, AND HEWITT
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sdo
cum
ent
isco
pyri
ghte
dby
the
Am
eric
anPs
ycho
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eof
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ishe
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ticle
isin
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edso
lely
for
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ofth
ein
divi
dual
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and
isno
tto
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ssem
inat
edbr
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the significant deviation contrast for that partic-ular location with respect to purposive listening.In contrast, significantly lower scores than theoverall mean were associated with being at arestaurant and pub/club for this type of listening(i.e., indicating that the music does not moti-vate, etc.).
Data on the consequences of music were alsoconsidered in the context of Mehrabian andRussell’s (1974) Pleasure–Arousal–Dominanceframework via three GLMM analyses (� �.017). Each analysis was based on one of thethree consequence factors (and the ratings ofchoice, liking, and arousal were entered as pre-dictor variables). Prior to analysis, factor scoreswere squared and then the root of the productwas obtained so that the analysis concernedonly the magnitude of the factor score ratherthan its direction (see Table 13). None of thethree domains were significantly associatedwith validation-seeking listening. Liking wasthe single negative predictor for actively en-gaged listening. Though potentially counterin-tuitive that liking for music demonstrated a neg-ative relationship with actively engagedlistening, this analysis focused on the magni-tude of the perceived consequence (as opposedto whether it was positively or negatively per-ceived), so it is perhaps indicative of a prefer-ence for moderate as opposed to extreme stim-uli.
For purposive listening, all three predictorswere significant: liking was negatively associ-ated, while arousal and choice were positivelyassociated with purposive listening. The nega-tive association between liking and purposivelistening suggests that liking for music meansthat it may actually represent a distraction. Thatchoice was a significant predictor indicates thatdominance is indeed an important component toresponses to music in everyday listening loca-tions. Mehrabian and Russell (1974) suggestedthat locations conducive to exerting controlwould be met with positive responses, and itseems that this is true for the purposive conse-quence, as the association was positive. Find-ings concerning purposive listening also appearto demonstrate the use of music to achievedifferent arousal states. In the light of this, it isinteresting that this reason was particularlyprominent among listening episodes that oc-curred at the gym.T
able
8G
LM
MA
naly
ses
Pre
dict
ing
the
Con
sequ
ence
sof
Lis
teni
ngU
sing
Tim
ean
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ion
Typ
e
Pred
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r
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osiv
elis
teni
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ely
enga
ged
liste
ning
Val
idat
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ing
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ning
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247MUSIC AND LOCATION
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ghte
dby
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edso
lely
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ofth
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and
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General Discussion
In western society, music is experienced in awide range of locations in people’s daily lives.The present study illustrated that where musicexperiences occur interacts with when they takeplace and how they take place. Results indicatethat the time of day and day of week do influ-ence where music is experienced in daily life.Additionally, younger individuals and thosewho spend more time listening to music onaverage experience more music in public set-tings.
Although music was experienced more oftenin private locations than in public overall, inter-esting patterns of music experiences that oc-curred in public locations demonstrate in detailhow music listening differs by location. In fact,a perceived lack of control does not necessarilycharacterize all of the episodes that occurred inpublic—differing locations gave rise to a di-verse use of devices and selection methods (ad-dressing research question 3). In public, peo-ple’s listening appears to be dominated by theuse of mobile listening devices, such that theseexperiences occur under one’s own control.Mobile mp3 and telephone use accounted for
44.3% of all public music experiences, far ex-ceeding both recorded and live public musicwhich supports the idea that listeners are usingdigital technology to create a private spacewithin a public space (Bull, 2007; Skånland,2011). In particular, use of different technology,such as mobile devices, allows for many selec-tion behaviors to be possible in locations inwhich a person may not have previously hadcontrol over their auditory environment.
Location-based differences may be in partdue to the range of device and selection optionsavailable in a particular setting. For instance,whereas all of the possible devices included inthe research were used on at least one recordedoccasion at home (where there are many devicesand selection methods that may be used to ex-perience music), 98.6% of music experiences onpublic transportation (a location with feweravailable options) involved mobile telephonesand mp3 players. This same reasoning appliesin the other contexts as well. For instance, ahigh frequency of music experiences that oc-curred at the gym did so via playlists and shuffleon a mobile device, while prerecorded broad-casted music accounted for a high frequency of
Table 9Estimated Means, Standard Errors, and 95% Confidence Intervals of the GLMM Analyses Concerning theSignificant Interactions Pertaining to Predicting the Consequences of Hearing Music
Outcome variable Interaction variables M SE 95% CI
Purposive listening Weekday Private �0.05 0.06 [�0.17, 0.06]Public 0.13 0.12 [�0.11, 0.37]
Weekend Private 0.08 0.11 [�0.14, 0.30]Public �0.27 0.15 [�0.56, 0.03]
Actively engaged listening 8:00–8:59 Weekday 0.05 0.10 [�0.15, 0.25]Weekend 0.71 0.14 [0.45, 0.98]
9:00–16:59 Weekday �0.07 0.06 [�0.18, 0.05]Weekend �0.23 0.12 [�0.47, 0.01]
17:00–20:59 Weekday �0.04 0.09 [�0.22, 0.13]Weekend 0.14 0.12 [�0.10, 0.38]
21:00–23:59 Weekday 0.09 0.16 [�0.21, 0.40]Weekend 0.05 0.37 [�0.68, 0.77]
Actively engaged listening 8:00–8:59 Private 0.22 0.17 [�0.11, 0.55]Public 0.54 0.07 [0.40, 0.68]
9:00–16:59 Private 0.12 0.06 [0.00, 0.24]Public �0.42 0.13 [�0.66, �0.17]
17:00–20:59 Private 0.08 0.09 [�0.09, 0.26]Public 0.02 0.14 [�0.26, 0.29]
21:00–23:59 Private �0.06 0.10 [�0.26, 0.14]Public 0.20 0.37 [�0.53, 0.94]
Note. N � 968.
248 KRAUSE, NORTH, AND HEWITT
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rs.
Thi
sar
ticle
isin
tend
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lely
for
the
pers
onal
use
ofth
ein
divi
dual
user
and
isno
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inat
edbr
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Tab
le10
Pai
rwis
eC
ontr
asts
Con
cern
ing
the
GL
MM
Ana
lyse
sP
redi
ctin
gth
eC
onse
quen
ces
ofL
iste
ning
Usi
ngT
ime
and
Loc
atio
nT
ype
Ana
lysi
sPa
irw
ise
Con
tras
tst
95%
CI
�2
Purp
osiv
elis
teni
ngPr
ivat
eW
eekd
ay–W
eeke
nd�
1.20
[�0.
35,
0.09
].0
01Pu
blic
Wee
kday
–Wee
kend
2.31
�[0
.06,
0.73
].0
05A
ctiv
ely
enga
ged
liste
ning
Wee
kday
Pre
wor
k(8
:00–
8:59
)–W
ork
day
(9:0
0–16
:59)
1.12
[�0.
09,
0.32
].0
01Pr
ew
ork
(8:0
0–8:
59)–
Aft
erw
ork
(17:
00–2
0:59
)0.
74[�
0.15
,0.
33]
.001
Pre
wor
k(8
:00–
8:59
)–L
ate
nigh
t(2
1:00
–23:
59)
�0.
27[�
0.37
,0.
28]
.000
Wor
kda
y(9
:00–
16:5
9)–A
fter
wor
k(1
7:00
–20:
59)
�0.
27[�
0.22
,0.
16]
.000
Wor
kda
y(9
:00–
16:5
9)–L
ate
nigh
t(2
1:00
–23:
59)
�1.
04[�
0.47
,0.
15]
.001
Aft
erw
ork
(17:
00–2
0:59
)–L
ate
nigh
t(2
1:00
–23:
59)
�0.
86[�
0.44
,0.
17]
.001
Wee
kend
Pre
wor
k(8
:00–
8:59
)–W
ork
day
(9:0
0–16
:59)
5.45
���
[0.6
0,1.
28]
.028
Pre
wor
k(8
:00–
8:59
)–A
fter
wor
k(1
7:00
–20:
59)
3.06
��
[0.2
0,0.
94]
.009
Pre
wor
k(8
:00–
8:59
)–L
ate
nigh
t(2
1:00
–23:
59)
1.70
[�0.
10,
1.43
].0
03W
ork
day
(9:0
0–16
:59)
–Aft
erw
ork
(17:
00–2
0:59
)�
2.16
�[�
0.71
,�
0.03
].0
04W
ork
day
(9:0
0–16
:59)
–Lat
eni
ght
(21:
00–2
3:59
)�
0.74
[�1.
01,
0.45
].0
01A
fter
wor
k(1
7:00
–20:
59)–
Lat
eni
ght
(21:
00–2
3:59
)0.
24[�
0.67
,0.
86]
.000
Priv
ate
Pre
wor
k(8
:00–
8:59
)–W
ork
day
(9:0
0–16
:59)
0.59
[�0.
24,
0.45
].0
00Pr
ew
ork
(8:0
0–8:
59)–
Aft
erw
ork
(17:
00–2
0:59
)0.
75[�
0.22
,0.
50]
.001
Pre
wor
k(8
:00–
8:59
)–L
ate
nigh
t(2
1:00
–23:
59)
1.49
[�0.
09,
0.66
].0
02W
ork
day
(9:0
0–16
:59)
–Aft
erw
ork
(17:
00–2
0:59
)0.
36[�
0.15
,0.
22]
.000
Wor
kda
y(9
:00–
16:5
9)–L
ate
nigh
t(2
1:00
–23:
59)
1.55
[�0.
05,
0.41
].0
02A
fter
wor
k(1
7:00
–20:
59)–
Lat
eni
ght
(21:
00–2
3:59
)1.
27[�
0.08
,0.
37]
.002
Publ
icPr
ew
ork
(8:0
0–8:
59)–
Wor
kda
y(9
:00–
16:5
9)7.
87���
[0.7
2,1.
19]
.057
Pre
wor
k(8
:00–
8:59
)–A
fter
wor
k(1
7:00
–20:
59)
3.92
���
[0.2
6,0.
78]
.015
Pre
wor
k(8
:00–
8:59
)–L
ate
nigh
t(2
1:00
–23:
59)
0.91
[�0.
39,
1.07
].0
01W
ork
day
(9:0
0–16
:59)
–Aft
erw
ork
(17:
00–2
0:59
)�
2.49
�[�
0.77
,�
0.09
].0
06W
ork
day
(9:0
0–16
:59)
–Lat
eni
ght
(21:
00–2
3:59
)�
1.64
[�1.
36,
0.13
].0
03A
fter
wor
k(1
7:00
–20:
59)–
Lat
eni
ght
(21:
00–2
3:59
)�
0.49
[�0.
93,
0.56
].0
00
�p
�.0
5.��
p�
.01.
���
p�
.001
.
249MUSIC AND LOCATION
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ofth
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restaurant episodes. These results demonstratethat although there are many ways that music isaccessed and heard, the pattern of usage is de-pendent on the specific options available in agiven context and the suitability of those op-tions for use during the task at hand therein.
These results have practical implications forthe marketing of music and of listening devices.For instance, it is easy to understand the recentincrease in sales of noise-cancelling and higherquality headphones in light of the increase inmobile music listening potentially occurring inpublic spaces. Additionally, this work has im-plications for the music information retrievalcommunity and those designing music recom-mendation programs and applications. Develop-ers wanting to tailor the listening experienceneed to account for where, how, and why peopleare listening. The inclusion of these sorts ofvariables will improve and extend current lis-tening recommendation systems, and provide adegree of control over contextualized music lis-tening that the present results indicate will havebeneficial consequences for users and applica-tion developers alike. Furthermore, as mobiledevices of ever-greater capacity become in-creasingly common, people’s ability to access arange of music will increase further: mobiledevices (and associated listening applications)will continue to shape everyday listening be-haviors both in public and private settings.
Choice, Attention, Liking, and Arousal
Research question 4 considered choice, atten-tion, liking, and arousal ratings of the music interms of the location of the music experience.The high choice ratings at home and driving acar support the contention that people have ahigh degree of dominance over music experi-ences in private spaces. However, while it wasexpected that individuals would exert a greaterdegree of choice over music experiences in pri-vate locations than in public locations, the pat-tern of significant contrasts demonstrated thatthe specific context was more important thanthis broad categorization of privacy. The highmeans and significant contrasts regardingchoice and attention ratings for public transpor-tation and walking (two public locations) dem-onstrate that in these situations, people mayactively choose what they would like to hear,creating a personal (and private) “audio bubble”T
able
11G
LM
MA
naly
ses
Con
cern
ing
Tim
ean
dSp
ecifi
cL
ocat
ions
Pre
dict
ing
the
Con
sequ
ence
sof
Lis
teni
ng
Pred
icto
r
Purp
osiv
elis
teni
ngA
ctiv
ely
enga
ged
liste
ning
Val
idat
ion-
seek
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F�
p2F
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250 KRAUSE, NORTH, AND HEWITT
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dby
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rather than listening to the world around one-self. With such relatively high ratings of choice,it is intuitive that the music would be well liked,not only because it is chosen over the ambientsounds of the natural surroundings but also be-cause the listener personally selects it. It isinteresting that in this digital era, these publiclocations appear to have supplanted the homeand concert hall as locations in which peoplemight go to listen most attentively to music. Incontrast, choice ratings corresponding to restau-rants and pubs/clubs were significantly lowerthan the overall mean— both public spaces,where listening to one’s own music may not besocially sanctioned. It is tempting to speculatethat music experiences in such settings fulfill abackground function, thereby demanding lessattention than when music is the focus of thesituation.
When considering the devices most likelyto be used in the different locations, the pat-tern of results concerning choice ratings be-comes clearer: the travel-related public loca-
tions were dominated almost entirely by mp3players and mobile phones, whereas restau-rant and pub/club locales were dominated bybroadcasted recorded music. In this context, itis interesting to consider whether choice rat-ings reflect the dominance dimension in Meh-rabian and Russell’s (1974) model. These re-sults suggest that a user’s level of input(dominance via choice/control) may well in-fluence how music is received in public. Inturn, Sloboda’s (2005) observation that indi-viduals encountered unchosen music in publicholds true when considering restaurant, pub,and club environments, but the increasingprevalence of mobile listening is apparentlychanging the auditory landscape of publicspaces. Using various technologies, listenersare able to exert dominance over their listen-ing in different contexts (including those out-side their homes), and this has the potential toalter how music is perceived in different lo-cations. Consequently, Bull’s (2007) notionof music as a “digital Sherpa” may be more
Table 12Deviation Contrasts Pertaining to the Location Main Effect forPurposive Listening
Deviation contrasts
Purposive listening
t 95% CI �2
At home—mean 0.09 [�0.17, 0.19] .000At a friend’s house—mean 0.29 [�0.27, 0.37] .000At work—mean 0.11 [�0.37, 0.42] .000At the gym—mean 5.58��� [0.77, 1.60] .029Driving a car—mean 0.29 [�0.24, 0.33] .000In a car—mean �0.39 [�0.44, 0.29] .000Public transportation—mean 0.10 [�0.29, 0.32] .000Walking—mean �0.35 [�0.63, 0.44] .000Restaurant—mean �2.03� [�1.07, �0.02] .004Pub/Club—mean �2.21� [�1.01, �0.06] .005Other—mean �0.38 [�0.48, 0.32] .000
� p � .05. �� p � .01. ��� p � .001.
Table 13GLMM Analyses Concerning the PAD Model Domains Predicting the Consequences of Listening
Predictor
Purposive listening Actively engaged listening Validation-seeking listening
F �p2 F �p
2 F �p2
Liking F(1, 1034) � 24.73, p � .001 .023 F(1, 1034) � 6.19, p � .001 .006 F(1, 1034) � 3.21, p � .073 .003Arousal F(1, 1034) � 23.71, p � .001 .022 F(1, 1034) � 1.64, p � .201 .002 F(1, 1034) � 0.12, p � .725 .000Choice F(1, 1034) � 13.06, p � .001 .012 F(1, 1034) � 0.18, p � .674 .000 F(1, 1034) � 0.38, p � .541 .000
Note. N � 1038.
251MUSIC AND LOCATION
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representative of people’s experiences in pub-lic, especially when traveling. This findingalso supports the conclusions of prior re-search, like that by Skånland (2011), whichshowed that participants valued being able toexert control over their auditory experiencewhile in public. In this way, one’s dominanceover music in a particular context may con-tribute to approach-avoidance behaviors, suchas willingness to remain within the environ-ment, and one’s broad emotional response tothat environment.
Choice and liking demonstrated a similar pat-tern of responses, which suggests that these twovariables are associated (and indeed the Pearsoncorrelation between them was significant:r(1073) � .56, p � .01), such that the ability tocontrol one’s listening might directly affect en-joyment of the music. Overall, mean liking rat-ings were high across the different locations:seven of the 11 locations gave rise to meanliking ratings �5 (on a 7-point scale), indicatingthat most of the music encountered, whether inpublic or private spaces, was received posi-tively. Contrary to criticisms that music encoun-tered in public might be unwanted and intrusive(Skånland, 2011), these results showed that al-though generally less-liked than in other loca-tions, music experienced in restaurants, pubs,and clubs (public contexts) was nonetheless notnecessarily disliked.
As for arousal, the significant contrastsdemonstrate that differences may be due tothe different functions that music fulfills indifferent settings by helping people to achievegiven levels of arousal. For instance, the am-bient music at a restaurant has a differentfunction than does music listened to at thegym for the purposes of motivation. Broadly,the findings support the notion that whilepeople may use music to achieve differentarousal states, their motivations may not al-ways be based on moderating their arousallevels. In particular, arousal optimization is amore likely explanation for the high ratingsgiven at the gym, consistent with prior re-search (North & Hargreaves, 1996c, 2000).Collectively, it appears that ratings of arousal,as well as choice, liking, and attention areassociated with the location in which the lis-tening takes place; thus, the notion of arousaloffers a direction for future research.
Consequences of Hearing Music
The fifth research question concerned theconsequences of hearing music. Although priorresearch demonstrated that motivations for mu-sic listening were situation dependent (North etal., 2004), the present results demonstrate that,regardless of intentions, the consequences ofeveryday exposure to music are subject to aninterplay of location and time. In general, thenature of the consequences experienced indi-cates that music is not only experienced as anentertainment pursuit. Moreover, the analysisconcerning the extent to which listening conse-quences could be predicted by ratings of liking,arousal, and choice supports the contention thatMehrabian and Russell’s model may be a usefulframework to use when explaining everydaylistening experiences. That choice was signifi-cantly related to the purposive consequencetype of listening extends the argument that con-trol is related to music experiences in everydaylife. Although not a direct test of Mehrabian andRussell’s model, the findings lend support to theidea that this model might apply to music lis-tening. Indeed, future research could directlyconsider Mehrabian and Russell’s model to bet-ter define choice and control in a musical con-text.
Limitations and Future Research
All participants resided in the United King-dom and used their personal mobile phone toparticipate. Therefore, while the results presentan overview of the role of location in everydaylistening in the United Kingdom (and likely theWestern world), they may not generalize toother geographic areas. For instance, the highprevalence of the radio in music listening maybe a consequence of using a sample residing inthe United Kingdom. Although location wasconsidered in terms of the immediate context, itis possible that the broader geographic regionplays a role as well, and in particular, futurecross-cultural research could address differ-ences in how people experience music in every-day life by comparing Western with non-Western experiences. For instance, theprevalence of using the Internet and mobiletelephones to access music may vary by geo-graphic location. Similarly, cultural factorswould likely impact on the specific pieces that
252 KRAUSE, NORTH, AND HEWITT
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the individual selects to hear in a given location:the specific music that an individual in oneculture finds, for example, calming would al-most certainly be from the music that an indi-vidual from a different musical culture finds tohave the same effect (e.g., North & Davidson,2013). Moreover, it will be important for futureresearch to consider individual differences. Ageand hearing ability may very well interact withthe location in which an individual spends time(the proclivity to be in certain contexts, exercis-ing at a gym, or on public transportation, forinstance) and/or with the devices involved inplaying music. In terms of the technology used,we equated “modern technology” with “digitaltechnology,” but it would also be interesting tosee whether people’s relationship to the formerwould be the same as their relationship with thelatter.
Similarly, the consequences of listeningcould be considered in terms of a person’sreasons/intentions for listening as well (Lon-sdale & North, 2011), so that the listeningexperience may also depend on that person’suse of music, and research on the relationshipbetween personality and musical taste (e.g.,North, 2010) suggests that the “big five” per-sonality factors also ought to mediate thespecific music selected in given locations.Future location-based research could also ad-dress music and emotion, which researchershave argued should be undertaken in naturalcontexts using methods such as experiencesampling methods (Eerola & Vuoskoski,2013). It seems likely that, as the conse-quences of listening were dependent on vari-ables such as time and location, so too wouldbe individuals’ emotional responses. More-over, if participants indicated that no musicwas heard, they did not provide further infor-mation for that episode: while this minimizeddemands on participants, it seems prudent thatfuture research should consider how listeningepisodes might otherwise differ from nonmu-sical episodes. Finally, future research mightconsider how the present results map onto aconsideration of music creation in everydaylife. For instance, does the degree of choiceand volition that one has over one’s music-making have implications for other responses,such as enjoyment and motivation to perse-vere?
Conclusion
The results of this study suggest that, ratherthan focusing simply on where everyday lis-tening occurs, a more informative approach tounderstanding the role of location in musiclistening is to also consider the listening con-text as including the device that music isplayed through and the individual’s percep-tion of control over it (as a measure of dom-inance). The significant findings concerningparticipants’ ratings of choice, attention, lik-ing, and arousal regarding the music experi-enced also demonstrated the role of these aspotentially important elements of context,particularly in the case of music experiencesthat occurred in public. The influence of mo-bile listening devices on people’s ability tocontrol their soundscapes was evident, as thepositive responses that resulted when portabledevices were used (i.e., high choice, attention,and liking ratings) contrasted sharply withthose recorded in response to music broad-casted publicly. The results concerning theperceived consequences of hearing music alsoindicate the importance of context, suggestingthat music functions in different ways de-pending on the specific characteristics of thesituation in which it is heard.
Overall, the data indicate that music is em-bedded within people’s everyday routines. Itappears that these routines have not been alteredto accommodate music, but that the prolifera-tion of music listening devices has allowed forthe inclusion of music within the stream of dailyWestern life. Therefore it is not so much thatdaily life has changed, but rather that a musicalsoundtrack has become embedded within it. AsO’Hara and Brown (2006) stated, “the way weconsume music is not simply about listening butinvolves the ways it becomes integrated into ourpersonal and social lives” (p. 3). This was mostevident in the present study through the use ofmusic while traveling. Not only in the car, butalso on public transportation and while walkingthrough public locales, individuals are able tocreate and control auditory soundtracks via mo-bile listening devices. Attention must be paid tothe means by which everyday music consump-tion is shaped by people’s ability to control andactively use music as a resource.
253MUSIC AND LOCATION
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(Appendix follows)
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Appendix
Response Entry
Time that the text message was received: _________________________Time when completing this entry: ___________________________x Tick here if you did not hear music within a 2-hr period prior to receiving the text message.If you heard music multiple times within the 2-hr block prior to receiving the text message,
please fill out this entry about the most recent listening episode.
Directions. Please select what best applies and mark only one answer.
Where were you? How did you hear the music?____ At home ____ Mobile mp3 player____ At a friend’s house ____ Mobile telephone____ At work ____ Mobile gaming device____ Driving a car ____ Mobile CD player____ In a car ____ Mobile cassette player____ Public transportation ____ Computer—own collection (iTunes, Winamp, etc.)____ Walking ____ Computer—online streaming (Spotify, LastFM, etc.)____ Restaurant ____ Stereo—mp3 device____ Shopping ____ Stereo—CD____ Religious worship ____ Stereo—cassette____ Pub/Club ____ Stereo—record____ Concert ____ Radio____ At the gym ____ TV____ Other: (please state below) ____ In public—live artist/group/ensemble________________ ____ In public—recorded music
How did you select what you heard?____ I did not have any control ____ Premade playlist—your own____ Someone I was with chose ____ Premade playlist—made by someone else____ Specific artist ____ Created a playlist at the time____ Specific album ____ Listened to the radio____ Specific song ____ Watched TV____ Random/shuffle ____ Downloaded from the Internet____ It was performed live at the time ____ Other: ____________________
How much choice did you have in what you heard?
None __1 __2 __3 __4 __5 __6 __7 Total
How much attention were you paying to the music?
None __1 __2 __3 __4 __5 __6 __7 Total
How much did you like what you heard?
Dislike very much __1 __2 __3 __4 __5 __6 __7 Like very much
(Appendix continues)
256 KRAUSE, NORTH, AND HEWITT
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How arousing was the music you heard?(Arousing in this case means how loud/fast/energizing/etc. was the music?)
Not at all __1 __2 __3 __4 __5 __6 __7 Highly arousing
The effect of this music was . . .
Please mark your answer on the scales below. If you feel that the music did not have the listedeffect, mark the middle, otherwise mark your answer closer to one of the two end points on eachof the scales.
It hindered myconcentration/thinking �3 �2 �1 0 1 2 3 It helped me to concentrate/think
It did not help to passthe time �3 �2 �1 0 1 2 3 It helped to pass the time
It prevented or lessenedan emotion
�3 �2 �1 0 1 2 3 It helped create or accentuate anemotion
It did not help theatmosphere
�3 �2 �1 0 1 2 3 It helped to create the “right”atmosphere
It did not motivate me �3 �2 �1 0 1 2 3 It motivated meIt hindered what I was
trying to do�3 �2 �1 0 1 2 3 It helped me with what I was trying
to doIt did not bring back
memories �3 �2 �1 0 1 2 3 It brought back memoriesIt made me look bad �3 �2 �1 0 1 2 3 It helped me look goodI learned nothing about
the music �3 �2 �1 0 1 2 3 I learned more about the musicIt annoyed me �3 �2 �1 0 1 2 3 I enjoyed itI wanted to get away
from the music�3 �2 �1 0 1 2 3 I wanted to hear the music for
longerIt hindered my worship �3 �2 �1 0 1 2 3 It helped me worshipOther (please specify) �3 �2 �1 0 1 2 3 Other (please specify)
Received January 9, 2014Revision received September 8, 2014
Accepted September 9, 2014 �
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