Mp3 Player Research Paper

Abstract


A crucial aspect of maintaining good mental health is to cope successfully with everyday stressors. This article explores the MP3 player as a technology of coping related to the stress of everyday life, in particular two common stressors in the urban environment: crowding and noise. The MP3 player has become a prime medium for everyday music listening, as individuals can carry a vast amount of music with them wherever they go. This unprecedented availability of music raises questions about its impact on the listener, or, as I will refer to him/her, the music user. In order to better understand the effects of this use, this article asks: how are mobile music devices used as a coping resource or device? The research presented here is based on twelve interviews with regular users of MP3 players who live or work in an urban environment. In fusing research on portable music players with research on stress and coping, this article suggests that the MP3 player may be a valuable coping device, enabling music users to enhance their subjective well-being and mental health.


Keywords


Mp3-players, mobile music, stress, coping, well-being


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Abstract

Analogue to occupational noise-induced hearing loss, MP3-induced hearing loss may be evolving into a significant social and public health problem. To inform prevention strategies and interventions, this study investigated correlates of adolescents’ risky MP3-player listening behavior primarily informed by protection motivation theory. We invited 1687 adolescents (12- to 19-year old) of Dutch secondary schools to complete questionnaires about their MP3-player listening, sociodemographic characteristics and presumed psychosocial determinants of MP3-player listening. Of all participants, 90% reported listening to music through earphones on MP3 players; 28.6% were categorized as listeners at risk for hearing loss due to estimated exposure of 89 dBA for ≥1 hour per day. Compared with listeners not at risk for hearing loss, listeners at risk were more likely not to live with both parents, to experience rewards of listening to high-volume levels, to report a high habit strength related to risky MP3 listening, and were less likely to be motivated to protect their hearing. Habit strength was the strongest correlate of risky listening behavior, suggesting that voluntary behavior change among adolescents might be difficult to achieve and that a multiple strategy approach may be needed to prevent MP3-induced hearing loss.

Introduction

There is an increasing population at risk of permanent, irreversible hearing loss and tinnitus due to increasing portable music player use, particularly MP3 players and equivalent devices, and the possibility to use such players at high sound levels [1, 2]. In their use of MP3 players, adolescents are very likely to engage in risky listening behaviors and are unlikely to seek protection [3]. Analogue to occupational noise-induced hearing loss, MP3-induced hearing loss may be evolving into a significant social and public health problem [1], which justifies the development and implementation of strategies for prevention and intervention.

To develop effective, interventions for hearing loss prevention due to risky MP3-player listening, more insight is needed into psychosocial correlates of such listening [4]. Hence, we aimed to identify important psychosocial correlates of risky MP3-player listening behavior—listening for ≥1 hour per day to a sound level of 89 dBA [1]—in a representative sample of adolescents.

We selected the protection motivation theory (PMT) as the most appropriate theoretical framework to study psychosocial correlates because it explains the cognitive processes that are used when people receive health information and has been proven reliable in predicting health-related intentions and behaviors in a variety of contexts [5–7]. According to the PMT, health protective, safe, behavior (or the ‘adaptive response’ a person engages in) is directly influenced by protection motivation, which is the result of an evaluation of environmental and personal factors. PMT posits that the probability of an adaptive response—in this case behavior to prevent hearing loss—is increased by four beliefs: the threat is perceived as severe (severity) and as of high personal relevance (vulnerability), the adaptive response is perceived as effective for warding off the threat (response efficacy), and the personal abilities and self-confidence to engage in the adaptive response is perceived as high (self-efficacy). However, the probability of an adaptive response is decreased by the perceived rewards of a maladaptive response, i.e. enjoying high-volume music on MP3 players [7].

We also explored the relevance of two extra constructs that might be important to consider when developing interventions. The first is ‘consideration of future consequences’ (CFC) [8]. This construct was included because it influences PMT constructs such as vulnerability and self-efficacy. A previous study found that although participating adolescents appeared to be generally aware of the risks of exposure to loud music, they expressed low personal vulnerability to music-induced hearing loss [9]. A factor that might influence beliefs about personal vulnerability is the extent to which an individual can imagine negative occurrences in the distant future. A general tendency to disregard future consequences may prevent an individual from feeling particularly vulnerable [8].

The second additional construct of which the relevance was explored is ‘habit strength’. This construct was included because previously it was found that adolescents’ MP3-player listening may be a kind of habitual behavior for which no intentional thinking is required [3].

The aim of this study was to investigate PMT-based constructs as well as CFC and habit strength as correlates of risky MP3-player listening among adolescents.

Methods

Participants

In 2007, a convenience sample of 1687 adolescents aged 12–19 years in 68 classes of 15 Dutch secondary schools were invited to complete questionnaires on sociodemographic factors, MP3-listening behavior, PMT constructs, considerations of future consequences, and habit strength; these questionnaires were completed under supervision (by IV and a teacher) at school. Adolescents and parents received written information about the study; parents could refuse their child's participation; participation by adolescents was voluntary and anonymous. This study was approved by the medical ethics committee of Erasmus MC, University Medical Center, Rotterdam, and has confirmed to the principles embodied in the Declaration of Helsinki.

Survey

The appendix to this paper presents the survey items on the sociodemographic factors, MP3-listening behavior, PMT constructs, and habit strength.

Ethnicity (Dutch or Western migrant; non-Western migrant) was determined on the basis of mother's and father's country/countries of birth according to the definitions of Statistics Netherlands [10]. The adolescent was of non-Western ethnic origin if at least one of the parents was born in a non-Western country. If both parents were born in a non-Western country, the country of birth of the mother decided on the ethnicity.

Habit strength was measured by asking the adolescents whether they agreed with statements on two of the three primary features of habitual behavior [11]: (i) automaticity and (ii) the sense of identity the behavior reflects. The third feature, the repeated character of the behavior (‘Playing music on my MP3 player at a very high volume is something I do very often’.) was excluded to avoid a too high correlation between habit strength and the outcome measure, since the frequency of use is also included in the calculation of the outcome measure.

Adolescents’ appreciation of their future was assessed using the Dutch version of the 12-item ‘CFC scale’ [8, 12]. This scale refers to the extent to which individuals consider the potential distant outcomes. Statements have to be rated such as ‘Often I engage in a particular behavior in order to achieve outcomes that may not result for many years’ and ‘I think that sacrificing now is usually unnecessary since future outcomes can be dealt with at a later time’.

All items related to the PMT constructs, CFC, and habit strength were measured by asking the adolescents to rate their agreement with each item on a bipolar five-point scale (−2 = not at all and +2 = completely). For constructs assessed with multiple items, the mean score was calculated after sufficient internal consistency was established, with positive scores indicating high levels of the construct. Internal consistency was assessed with Cronbach's alpha. For a short scale, Cronbach's alpha should be >0.70 [13]. Table I presents data on the number of scale items, range, and internal consistency for each construct.

Table I.

Number of scale items, internal consistency and interpretation of high scores for the PMT and additional constructs

Psychosocial constructs Number of itemsaCronbach's alpha Association with risk behaviorb
CFC 12 0.79 − 
PMT 
    Rewards maladaptive response 0.83 
    Severity 0.75 − 
    Vulnerability NAc− 
    Response efficacy 0.69 − 
    Self-efficacy NAc− 
    Protection motivation 0.85 − 
   Habit strength 0.87 
Psychosocial constructs Number of itemsaCronbach's alpha Association with risk behaviorb
CFC 12 0.79 − 
PMT 
    Rewards maladaptive response 0.83 
    Severity 0.75 − 
    Vulnerability NAc− 
    Response efficacy 0.69 − 
    Self-efficacy NAc− 
    Protection motivation 0.85 − 
   Habit strength 0.87 

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Risky MP3-player listening

Within current European occupational safety standards [14], noise levels equal to or exceeding the equivalent of 80 decibels (dBA) for 40 hours per week are assumed to be potentially damaging. However, in the report of the Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR), it is assumed that listening to an MP3 player for 1 hour a day to a sound level of >89 dBA is potentially damaging. By applying the principle that a doubling in level (+3 dBA, as dBA have a logarithmic scale) can be offset by halving the permissible exposure duration, a permissible exposure limit (PEL) can be calculated for each individual sound level expressed in dBA [15]. Exposure to a level of 89 dBA for 1 hour per day is thus assumed to be equivalent to the exposure to 92 dBA for 1.5 hour and 86 dBA for 2 hours per day. As another example, by applying this principle, it can be calculated that listening 7 hours per week (=1 hour per day) to a music level of 89 dBA is equal to listening for 56 hours per week to a music level of 80 dBA.

To estimate a weekly MP3-player listening dose on basis of reported exposure times and estimated dBA levels, we first calculated PELs for the estimated dBA levels of each participant per music source, using the equation PEL(week) = 56/2(L – 80)/3, where L stands for the estimated dBA level [15]. Second, each respondent's actual exposure time was divided by the PEL to compute his or her estimated weekly MP3-player listening dose [15]. To evaluate risk behavior, responses were dichotomized into adolescents who were considered not to be exposed to potentially hazardous music levels (dose <1; listening on average <1 hour per day to an equivalent music level of 89 dBA—‘listeners not at risk for hearing loss’) and those who were considered to be exposed to potentially hazardous music levels (dose ≥l; listening on average ≥1 hour per day to an equivalent music level op 89 dBA—‘listeners at risk for hearing loss’). Estimation of risky MP3-player listening previously has been described in more detail [2].

Statistical analyses

Statistical analyses were performed using the SPSS program (version 15; SPSS Inc., Chicago, IL). Frequency tables were used to explore the sociodemographic characteristics of the total study population (N = 1360), and those categorized as risk (n = 487) and not at risk (n = 873) for hearing loss. Mean and frequency differences of the total study population characteristics were examined through univariate analysis of variance and chi-square statistics, respectively. Zero-order correlations were calculated for all psychosocial variables to assess for multicollinearity and to explore associations between these variables. All correlations were under 0.75 (all P < 0.01), indicating that multicollinearity would not be an issue for multiple logistic regression analyses [16].

The NLMIXED procedure with the adaptive Gaussian quadrature integration method was used in SAS version 9.1.3 to check for clustering within school classes; this was not the case. To take into account the theoretical interrelations between the psychosocial constructs, a conceptual hierarchical framework was used. Hierarchical logistic regression analyses have been designed to test theoretical assumptions and to examine the influence of hierarchical levels of a conceptual framework in a sequential way [17]. Starting with Level 1, factors from the next hierarchical levels were stepwise added.

It was assumed that the sociodemographic factors would be the factors likely to directly or indirectly determine all proposed psychosocial factors. Therefore, in Step 1, the sociodemographic characteristics were entered. In Step 2, CFC was added to the analyses, of which the influence on listening behavior is mediated by PMT constructs such as vulnerability and self-efficacy. Therefore, in Step 3, the PMT constructs were included in the model. In Step 4, protection motivation was added to the model because it is expected to mediate between the PMT constructs and behavior. Finally in Step 5, habit strength was added. Omnibus tests of model coefficients indicated whether adding a block resulted in a significant increase of the explained variance. Any P values of <0.05 were considered to be statistically significant. When subsequent levels are added to the model, some significant upstream constructs (from a previous hierarchical level) may no longer have a significant direct effect on the behavior because of mediation; i.e. it is expected that in the final model CFC and the PMT constructs (added in steps 2 and 3) may no longer be significant.

Results

Participants

The response rate was 89.9%. Four questionnaires were excluded due to incomplete data. Of the 1512 participants, 89.9% reported to listen to music through earphones on MP3 players. Thus, 1360 questionnaires could be used in the analyses; 35.8% (n= 487) were categorized as listeners at risk for hearing loss. Table IIA gives an overview of the sociodemographic characteristics of the total study population.

Table II.

Characteristics of study population (N = 1360)

Charateristics Total Listeners not at riskaListeners at riskbP valuec
N = 1360 n = 873 n = 487 
A. Sociodemographic Frequency 
    Sex 
        Male 47.9% 46.8% 49.9% 
    Secondary education *** 
        Practical prevocational 18.5% 14.9% 24.8% 
        Theoretical prevocational 30.9% 28.9% 34.5% 
        Senior general secondary education 26.0% 27.7% 22.8% 
        Pre-university education 24.7% 28.5% 17.9% 
    Ethnicity *** 
        Non-Western migrant 13.5% 10.8% 18.3% 
    Home situation *** 
     Not living with both parents 17.7% 14.8% 22.8% 
Means (standard deviations) 
Age in years 14.7 (1.20) 14.7 (1.22) 14.9 (1.16) ** 
B. Psychosocial 
    CFC −0.01 (0.59) 0.07 (0.57) −0.17 (0.60) *** 
 PMT 
     Rewards maladaptive response −0.37 (0.99) −0.79 (0.78) 0.38 (0.89) *** 
     Severity 1.14 (0.61) 1.18 (0.57) 1.07 (0.68) ** 
     Vulnerability 0.86 (0.93) 0.97 (0.89) 0.65 (0.95) *** 
     Response efficacy 0.81 (0.86) 0.96 (0.78) 0.53 (0.92) *** 
     Self-efficacy −0.05 (1.09) 0.11 (1.03) −0.35 (1.14) *** 
      Protection motivation −0.50 (1.08) −0.15 (1.03) −1.14 (0.84) *** 
    Habit strength −0.21 (1.24) −0.82 (0.94) 0.87 (0.92) *** 
Charateristics Total Listeners not at riskaListeners at riskbP valuec
N = 1360 n = 873 n = 487 
A. Sociodemographic Frequency 
    Sex 
        Male 47.9% 46.8% 49.9% 
    Secondary education *** 
        Practical prevocational 18.5% 14.9% 24.8% 
        Theoretical prevocational 30.9% 28.9% 34.5% 
        Senior general secondary education 26.0% 27.7% 22.8% 
        Pre-university education 24.7% 28.5% 17.9% 
    Ethnicity *** 
        Non-Western migrant 13.5% 10.8% 18.3% 
    Home situation *** 
     Not living with both parents 17.7% 14.8% 22.8% 
Means (standard deviations) 
Age in years 14.7 (1.20) 14.7 (1.22) 14.9 (1.16) ** 
B. Psychosocial 
    CFC −0.01 (0.59) 0.07 (0.57) −0.17 (0.60) *** 
 PMT 
     Rewards maladaptive response −0.37 (0.99) −0.79 (0.78) 0.38 (0.89) *** 
     Severity 1.14 (0.61) 1.18 (0.57) 1.07 (0.68) ** 
     Vulnerability 0.86 (0.93) 0.97 (0.89) 0.65 (0.95) *** 
     Response efficacy 0.81 (0.86) 0.96 (0.78) 0.53 (0.92) *** 
     Self-efficacy −0.05 (1.09) 0.11 (1.03) −0.35 (1.14) *** 
      Protection motivation −0.50 (1.08) −0.15 (1.03) −1.14 (0.84) *** 
    Habit strength −0.21 (1.24) −0.82 (0.94) 0.87 (0.92) *** 

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Briefly, it shows that 43.8% of the listeners not at risk for hearing loss were attending pre-vocational schools, 10.8% were non-Western migrant, and 14.8% were not living with both parents. About 60% of the listeners at risk were attending pre-vocational schools, 18.3% were non-Western migrant, and 22.8% were not living with both parents (all P < 0.001).

Table IIB shows that all means of the psychosocial constructs between the groups of listeners differed in the expected direction as indicated in Table I (all P < 0.01).

Correlates of risky MP3-player listening

Table III presents results of the hierarchical multiple regression analyses. Adding each block resulted in a significant increase in percentages of explained variance.

Table III.

Multivariate ORs, 95% CIs and explained variance (Nagelkerke R2) from hierarchical multiple logistic regression analyses with risky MP3-player listeninga as dependent variable and demographic factors (Step 1), considering future consequences (Step 2), PMT constructs (Steps 3 and 4) and habit strength (Step 5) as independent variables

Model 1 Model 2 Model 3 Model 4 Model 5 
OR (95% CI) ORb (95% CI) ORb (95% CI) ORb (95% CI) ORb (95% CI) 
Demographic factors 
       Age in years 1.11 (1.01–1.23) 1.12 (1.02–1.24) 1.05 (0.94–1.18) 1.05 (0.93–1.19) 1.10 (0.96–1.26) 
       Male 1.02 (0.81–1.29) 0.96 (0.76–1.22) 0.84 (0.63–1.11) 0.83 (0.62–1.11) 0.78 (0.56–1.07) 
    Educational level 
        Practical pre-vocational 2.36 (1.64–3.39) 2.04 (1.41–2.96) 1.64 (1.05–2.58) 2.00 (1.25–3.19) 1.28 (0.77–2.13) 
        Theoretical pre-vocational 1.75 (1.27–2.41) 1.64 (1.18–2.27) 1.51 (1.03–2.23) 1.67 (1.12–2.49) 1.19 (0.77–1.85) 
        Senior general 1.32 (0.94–1.86) 1.27 (0.90–1.79) 1.21 (0.81–1.81) 1.32 (0.87–1.99) 1.20 (0.76–1.91) 
        Pre-university 1.00 1.00 1.00 1.00 1.00 
    Non-Western migrant 1.50 (1.07–2.09) 1.60 (1.14–2.25) 1.41 (0.94–2.12) 1.45 (0.95–2.21) 1.50 (0.96–2.36) 
    Not living with both parents 1.59 (1.18–2.15) 1.61 (1.19–2.18) 1.58 (1.10–2.27) 1.54 (1.06–2.24) 1.39 (0.92–2.08) 
CFC 0.48 (0.39–0.59) 0.81 (0.62–1.07) 0.90 (0.68–1.19) 1.17 (0.85–1.60) 
PMT constructs 
    Rewards maladaptive response 4.54 (3.74–5.52) 3.71 (3.04–4.53) 1.73 (1.36–2.20) 
    Severity 1.15 (0.89–1.48) 1.17 (0.90–1.52) 1.09 (0.82–1.45) 
    Vulnerability 1.03 (0.87–1.23) 1.06 (0.89–1.26) 1.06 (0.88–1.29) 
    Response efficacy 0.82 (0.68–0.99) 0.91 (0.74–1.11) 0.91 (0.73–1.14) 
    Self-efficacy 0.86 (0.74–0.99) 1.13 (0.96–1.33) 1.10 (0.92–1.33) 
     Protection motivation 0.46 (0.37–0.55) 0.60 (0.48–0.75) 
Habit strength 3.53 (2.85–4.37) 
Nagelkerke R20.056 0.104 0.440 0.486 0.592 
Model 1 Model 2 Model 3 Model 4 Model 5 
OR (95% CI) ORb (95% CI) ORb (95% CI) ORb (95% CI) ORb (95% CI) 
Demographic factors 
       Age in years 1.11 (1.01–1.23) 1.12 (1.02–1.24) 1.05 (0.94–1.18) 1.05 (0.93–1.19) 1.10 (0.96–1.26) 
       Male 1.02 (0.81–1.29) 0.96 (0.76–1.22) 0.84 (0.63–1.11) 0.83 (0.62–1.11) 0.78 (0.56–1.07) 
    Educational level 
        Practical pre-vocational 2.36 (1.64–3.39) 2.04 (1.41–2.96) 1.64 (1.05–2.58) 2.00 (1.25–3.19) 1.28 (0.77–2.13) 
        Theoretical pre-vocational 1.75 (1.27–2.41) 1.64 (1.18–2.27) 1.51 (1.03–2.23) 1.67 (1.12–2.49) 1.19 (0.77–1.85) 
        Senior general 1.32 (0.94–1.86) 1.27 (0.90–1.79) 1.21 (0.81–1.81) 1.32 (0.87–1.99) 1.20 (0.76–1.91) 
        Pre-university 1.00 1.00 1.00 1.00 1.00 
    Non-Western migrant 1.50 (1.07–2.09) 1.60 (1.14–2.25) 1.41 (0.94–2.12) 1.45 (0.95–2.21) 1.50 (0.96–2.36) 
    Not living with both parents 1.59 (1.18–2.15) 1.61 (1.19–2.18) 1.58 (1.10–2.27) 1.54 (1.06–2.24) 1.39 (0.92–2.08) 
CFC 0.48 (0.39–0.59) 0.81 (0.62–1.07) 0.90 (0.68–1.19) 1.17 (0.85–1.60) 
PMT constructs 
    Rewards maladaptive response 4.54 (3.74–5.52) 3.71 (3.04–4.53) 1.73 (1.36–2.20) 
    Severity 1.15 (0.89–1.48) 1.17 (0.90–1.52) 1.09 (0.82–1.45) 
    Vulnerability 1.03 (0.87–1.23) 1.06 (0.89–1.26) 1.06 (0.88–1.29) 
    Response efficacy 0.82 (0.68–0.99) 0.91 (0.74–1.11) 0.91 (0.73–1.14) 
    Self-efficacy 0.86 (0.74–0.99) 1.13 (0.96–1.33) 1.10 (0.92–1.33) 
     Protection motivation 0.46 (0.37–0.55) 0.60 (0.48–0.75) 
Habit strength 3.53 (2.85–4.37) 
Nagelkerke R20.056 0.104 0.440 0.486 0.592 

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In the first step, age, educational level, ethnicity, and home situation were significant correlates and explained 5.6% (Nagelkerke R2) of the variance of the risk behavior. For example, adolescents attending practical pre-vocational education were almost 2.5 times more likely to be listeners at risk than their pre-university counterparts [odds ratio (OR) 2.36; 95% confidence interval (CI) 1.64–3.39]. In the subsequent steps, when CFC (Step 2), the PMT constructs rewards of maladaptive response, severity, vulnerability, response efficacy, self-efficacy (Step 3) and protection motivation (Step 4) were added, the explained variance increased to 10.4%, 44.0% and 48.6%, respectively. Adolescents listening at risky music levels reported significantly less CFC, response efficacy, self-efficacy and protection motivation than those listening at lower music levels, and were more likely to experience rewards from the risk behavior. In the fifth and final step, when habit strength was included, the explained variance increased to 59.2%. None of the sociodemographic factors was significantly correlated with the risk behavior in the final model. Adolescents listening at risky levels were more likely to experience intrinsic rewards and less likely to be motivated to protect themselves than those listening at lower music levels. Furthermore, for those listening at risky music levels, listening to high-volume music was more often a habit than for those listening at lower levels (OR 3.53; 95% CI 2.85–4.37).

Discussion

Compared to MP3-player listeners not at risk, listeners at risk for hearing loss did not consider hearing protection in discotheques to be useful, had no confidence in their ability to change their behavior and did not intend to change their behavior. Listening to an MP3 player seems to be a common part of many adolescents’ lives for which no intentional thinking is required. This would explain why habit strength was the strongest psychosocial predictor of unsafe listening behavior.

Habit strength was the strongest correlate of risky listening behavior, supporting the hypothesis posed in a previous study [3]. It seems that MP3 listening among adolescents is a natural part of their everyday lives that does not require any intentional thinking to be set in motion [11]. This seems to be especially the case with adolescents who live in the ‘here and now’ and do not consider future consequences. The listeners at risk seemed not interested in considering future consequences; they seemed more concerned with maximizing immediate benefits and more influenced by the more immediate consequences such as ‘getting lost’ in the music, than by probabilistic future outcomes [8].

These findings suggest that voluntary behavior change among adolescents might be difficult to achieve, which confirms previous research [9, 18]. Although considered to be ultimately responsible, experts consulted in a Delphi study did not expect that adolescents in general would currently perform the necessary protective behaviors to prevent MP3-induced hearing loss [18], which is in accordance with opinions of adolescents themselves [9

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