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ARTICLE  
Year : 2014  |  Volume : 16  |  Issue : 72  |  Page : 292-298
Construction and validation of questionnaire to assess recreational noise exposure in university students

1 Department of Epidemiology, Public Health (Epidemiology) Program, School of Public Health, Universidad de Chile; Division of Epidemiology, UDA Ciencias de la Salud, Carrera de Fonoaudiología, Pontificia Universidad Católica de Chile, Santiago, Chile
2 Department of Epidemiology, Public Health (Epidemiology) Program, School of Public Health, Universidad de Chile; Department of Otolaryngology, Clínica Las Condes; Department of Otolaryngology, San Juan de Dios Hospital - Universidad de Chile, Santiago, Chile

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Date of Web Publication10-Sep-2014
 
  Abstract 

Recreational noise exposure and its impact on hearing is a problem to which increasing attention is being paid. In Spanish, it is necessary to have a reliable and valid instrument that is capable of describing the extent of noise exposure. The aim was to create and validate an instrument to determine listening habits and levels of recreational noise exposure in young people. We performed a transversal questionnaire validation study using university students. We assessed the validity of the content and appearance of the "Recreational Hearing Habits Questionnaire" (CHAR in Spanish) through experts' judgment. Then we piloted the administration of semantic adaptation with 30 students. Finally, the instrument was applied to 335 Chilean university students, obtaining with these indicators that demonstrated convergent validity of the construct, criterion and reliability. We used exploratory and confirmatory factor analysis, as well as correlation and agreement tests. It was confirmed that 14 questions in the questionnaire have a good item-test correlation, having also a factorial structure that indicates the existence of three-dimensions. The questionnaire has good internal consistency and convergent validity with the Noise Exposure Questionnaire. In addition, the score obtained in the CHAR is a predictor of the presence of notch at frequencies of 4 kHz in the right ear and 6 kHz in the left. The CHAR is useful for determining listening habits and thereby recreational noise exposure, indicating good psychometric properties.

Keywords: College students, noise induced hearing loss, recreational noise

How to cite this article:
Fuentes López EA, Morales FC. Construction and validation of questionnaire to assess recreational noise exposure in university students. Noise Health 2014;16:292-8

How to cite this URL:
Fuentes López EA, Morales FC. Construction and validation of questionnaire to assess recreational noise exposure in university students. Noise Health [serial online] 2014 [cited 2020 Oct 27];16:292-8. Available from: https://www.noiseandhealth.org/text.asp?2014/16/72/292/140509

  Introduction Top


Noise-induced hearing loss is the second most common cause of sensorineural hearing loss, preceded only by presbycusis (age-related hearing loss). [1] Initially, the focus of research in this field was to assess the public health impact of noise-induced hearing loss in occupational contexts. In recent years, however, it has been reported that a number of noise sources that are not work-related in nature (attending concerts, discotheques, etc.,) produce sounds in which brief exposure can generate permanent hearing damage. [2]

With respect to its prevalence, Niskar et al. [3] studied audiograms of children and adolescents who participated in the Third National Health and Nutrition Examination Survey (NHANES III), reporting that 12.5% (about 5.2 million) of respondents between the age rates of 6 and 19, showed evidence suggesting audiometric hearing loss induced by noise. Similarly, Rabinowitz et al. [4] observed that 16% of the audiograms of young adults between 17 and 25 years of age displayed high frequency hearing loss (sensitivity to noise). Shargorodsky et al. [5] compared the audiometric thresholds of North American adolescents in the NHANES survey during the years 1988-1994 with those obtained between 2005 and 2006, denoting the increase from 14.9% to 19.5% in the prevalence of hearing loss. In recent times, Henderson et al., [6] also based on the NHANES results, found that the prevalence of exposure to noise increased from 19.8% to 34.8% when listening to music through headphones in the prior 24 h.

In Chile, one of the first studies was conducted by Jofré et al., [7] who determined that 30% of young people surveyed were found to be exposed to noise levels above the threshold that is considered to be risky. The measurement was performed based on the "Noise Exposure Questionnaire" (CER in Spanish). [8] In this instrument, which is of Spaniard origin, the respondent is asked to indicate the number of days per week, hours per day, and the noise level recognized when attending various activities associated with the presence of noise (listening to music on MP3, attending concerts, etc.,). [8] Although the instrument was validated in their country of origin, the authors conducted a cultural adaptation of it, and no pilot application was made prior to its use with the study population. Recently, Breinbauer et al. [9] had reported that the population at risk of permanent hearing loss resulting from the use of portable music playback devices could reach 12%. These authors also used a questionnaire which did not consider other sources of recreational noise exposure such as attending nightclubs, pubs, karaoke or sports events that, according to the sound measurement, are all activities reported to have high noise levels. [10] In this way, the number of subjects that are at risk of noise-induced hearing loss has been underestimated.

Our study, consequently, aims to construct a valid and reliable instrument capable of assessing young people's recreational noise exposure including various contexts in which such exposure occurs.


  Methods Top


We conducted a cross-sectional validation study for the questionnaire in the period between August 1, 2011 and December 14, 2012. The participants were Chilean speech and language therapy students, who signed an informed consent for participating in the study. The protocol of the study had the approval of the University Ethics Committee.

Description of the CHAR questionnaire

The "Recreational Hearing Habits Questionnaire" (CHAR) is a self-administered instrument that aims to determine the listening habits of adolescents and young adults as well as the contexts of exposure to loud sounds of recreational nature. The CHAR originally included 24 closed format questions (three to five alternatives), in some cases with the help of images (question 2). Although questions are not grouped in items, it is possible to recognize the following aspects:

  1. Characteristics of personal music players, period, frequency and context of use;
  2. Attendance to concerts; and
  3. Attendance to other noisy venues. Each question has a maximum score of 5 points, assigned increasingly in relation to the noise level associated with each behavior or to the frequency.


The validation process of the instrument was performed including the following stages:

  1. Semantic adaptation,
  2. Validation of content and appearance,
  3. Reliability,
  4. Convergent validity, and
  5. Construct validation.


Validation of content and appearance

There was a team of nine experts on the subject from public, private and academic institutions, who evaluated the relevance of the selected indicators, as well as the form (appearance) that would be measured. We used the content validity ratio (CVR) proposed by Lawshe, [11] in which experts are asked to indicate whether each question included in the instrument is "essential" to operationalizing the construct. As the present study included nine experts, those questions with a CVR of less than 0.75 were eliminated.

Semantic adaptation

At this stage, we proceeded to adjust the first version of the questionnaire and then applied to a purposive sample of 30 university students. These young people had previously indicated whether or not a particular question with grammatical and semantic structure allowed for easy understanding. The questions and alternatives of the questionnaire were adapted based on feedback provided by these students.

Construct validation

The CHAR questionnaire was administered to a purposive sample of 335 students from a private university in the metropolitan area of Santiago. The age of respondents ranged between 18 and 35 years, with a mean age of 21.62.

Exploratory factorial analysis was used to validate the construct of the CHAR questionnaire. In order to confirm the factorial structure of the questionnaire, a confirmatory factor analysis was performed. This technique was justified since there is theoretical and in part, empirical evidence (based on previous applications of the instrument) on the dimensions of the variables studied. [12]

Convergent validation

Through the application, we jointly studied the CHAR questionnaire and the CER questionnaire. [8] It should be noted that although both questionnaires generally address the same problem, the questions differ in their formats. As for the analysis, correlations were obtained between the two instruments through coefficient correlation of Kendall Tau-b. For similar questions, the level of agreement was determined through the kappa coefficient.

Predictive validation

In order to determine whether there was an association between the score obtained in the CHAR questionnaire with the presence of notch in the high frequencies, we proceeded to perform an audiometric evaluation. This evaluation was performed in a silent cabin (sound-insulated and sound-dampened) with a calibrated Interacoustics AC40 audiometer (two-channel-clinical audiometer) according to ANSI S3.6. Tonal thresholds were measured at frequencies from 0.25 to 8 kHz, including interoctaves like frequencies of 3 and 6 kHz. These were determined according to ISO 8253-1, using a modification of the Hughson-Westlake procedure. [13] Since the audiometer has TDH-39 headphones, a 6 dB correction in the threshold was obtained in the frequency of 6 kHz to avoid the presence of artificial notch. [14] We determined the presence of notch according to the criteria proposed by Coles et al. [15] wherein the hearing threshold level in 3 and/or 4 and/or 6 kHz must be at least 10 dB greater than 1 kHz or 2 kHz and 8 kHz.

Statistical models were created using logistic regression, in which the response variable was the presence of notch in frequency 6 kHz as in 4 kHz for both ears, and the predictor variable score corresponded to CHAR.

Reliability

In order to determine the internal consistency of each questionnaire, we calculated the "Cronbach alpha" coefficient reliability. This was obtained from both of them for each question as to the dimensions identified from exploratory factor analysis. The "Cronbach alpha" coefficient may underestimate the reliability of the scale when there are no errors of covariance and in turn, in the presence of these errors, it may both underestimate and overestimate it. [12] Given this, the drive ability is also estimated based on the adjustments proposed by Raykov. [16]

Statistical analysis

We used the STATA program version 12 and the MPLUS program version 6.11(StataCorp. and Muthen & Muthen, respectively) The first was used to conduct exploratory factor analysis and statistical modeling using logistic regression. The second software was used for confirmatory analysis of factors. For the second analysis, we used as an estimator the weighted least squares means and variance adjusted, because the variables of the CHAR questionnaire are ordinal in nature. In addition, we indicated the censored nature of the distribution of the questionnaire responses.

In the case of logistic regression models, we assessed the adjustment criterion using the Hosmer-Lemeshow test. We considered a significance level of 5% for the performed hypothesis tests.


  Results Top


Validity index of content and appearance

The Lawshe CVR index identifies 16 of the 24 original CHAR questions with values above 0.75, on the level of both content and appearance [Table 1].
Table 1: Index of content validity and appearance of CHAR questions

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With this result, we adjusted the first version of the questionnaire, which was applied to 30 young people in pilot form. Finally, we applied a purposive sample of 335 university students, and the results allowed us to obtain indicators of validity of construct, concurrence and reliability.

Exploratory factor analysis

All questions achieved correlation coefficients with the total score of the questionnaire above 0.3 and below 0.9. Given the nature of the measurement of the instrument questions (ordinal), we obtained a polychoric correlation matrix. [17] This matrix is used for exploratory factor analysis, which showed the presence of three factors with an eigenvalue equal to or greater than one.

Factor 1 accounts for 49.5% of the explained variance and it saturates the six questions related to the use of portable music players. Factor 2 accounts for 24.3% of the variance and it saturates the three questions associated with attending concerts. Factor 3 accounts for 17.5% of the variance explained and saturates the questions with the attendance to other spaces that can be considered noisy.

In order to improve fitness to the application, we proceeded with the application of an orthogonal varimax rotation. Despite this, questions 15 and 16 showed a poor loading factor and a raised representation in more than one factor; therefore, it was eliminated.

[Table 2] shows the factor loadings after the rotation omitting those with values less than 0.4. In addition, we reported the Kaiser-Meyer-Olkin sampling adequacy index. Although there are values lower than 0.7 showing a diffusion of the correlation patterns, most of the questions are between 0.8 and 0.9, indicating a quite good fit for the sample for factor analysis. [18]
Table 2: Factor loadings and KMO index of the CHAR questions

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Confirmatory analysis of factors

The 14 CHAR questions were loaded on the three factors (items) identified in the exploratory analysis. In terms of the adjustment criterion of the planned model, the comparative fit index (CFI) was higher than the cut-off point corresponding to 0.95 proposed by Hu and Bentler, [19] reaching a value of 0.98. The Tucker-Lewis adjustment index (TLI) [20] was also high: 0.97. Moreover, the value of root mean square error of approximation (RSMEA) was 0.063, which is within the range of acceptable adjustment (0.05-0.08), [21],[22] finding the upper limit of the confidence interval (CI) (0.076) within that range. As for weight root mean square residual, it reached a level of 0.824, which also reports as a good fit. [12] However, the "close fit" test was statistically significant (P = 0.038) so it is possible to reject the hypothesis of a good adjustment. [23]

Considering the modification indices (MIs), we decided to free the associated error covariance of questions 3 and 8, of which the MI was 23.59. After generating a new model, we decided to also clear the covariance error between items 9 and 8 with a MI of 34.55. The final model has an adjusted CFI index of 0.99, the same value reached by the TLI index. The RSMEA value (0.042) is within what is considered to be a very good fit (<0.05). Additionally, the "close fit test" was not statistically significant (P = 0.816) meaning that it is not possible to reject the hypothesis of a good adjustment.

Finally, since the Chi-square test differences [24] proved to be significant (χ² diff (2) = 62.944, P < 0.001), we may conclude that the model with the two specified covariance errors provides a significantly better fit to the data compared with the model that did not include them.

[Table 3] shows that all standardized factor loadings were higher than 0.4. Regarding R2, it represents how much variance of the indicator (question) is explained by its specific factor [12] [Table 3].
Table 3: Standardized coefficients of the confirmatory factor analysis

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Convergent validity

Correlations with CER

We determined the correlation coefficient between the number of hours of weekly use of the player listed in the CER and the score obtained in question 8 of the CHAR (categorization of weekly use). For those users of at least one player, the coefficient corresponds to 0.35 (P < 0.001). As for the correlation between the number of hours of daily use of the player listed in the CER and the score obtained in question 9 of the CHAR (categorized) for users of at least one player, it corresponds to 0.61 (P < 0.001).

Regarding the use of portable music players, these devices are included in very general terms in the CER questionnaire, while the CHAR noted the differentiated between them (Mp3, Mp4, iPod, phone, etc.,) since there are differences in the compression system of the audio tracks of each device and thus, the possibility of reaching a certain maximum output may be different. [25] [Table 4] shows the correlation between weekly use in continuous form in the CER and the answer to question 8 of CHAR; and for each user of different types of music players, as well as the correlation to number of hours of daily use.
Table 4: Correlation coefficients between CER and CHAR questionnaires


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Agreement between CHAR and CER

The report agreement of use of portable music players (regardless of type) reached 95.1% with a κ equal to 0.75 (z = 12.22, P < 0.001). About 3.8% of students reported using music players in the CHAR, but omitted this information in the CER, whereas 1.1% of those who expressed using music players in the CER omitted it from CHAR.

The existing agreement on concert attendance report in both questionnaires reached 48.5%, with the κ index being equal to 0.076 (z = 3.25, P < 0.001). About 51.5% of the subjects reported attending concerts in the CHAR, but omitted this information in the CER, while there were no subjects that expressed attending concerts in the CER and then omitted this information from the CHAR.

The existing agreement on the attendance at other noisy venues (discotheques and bars) reached 80.3%, with the κ index being equal to 0.59 (z = 9.75, P < 0.001). 13.6% of the subjects reported attending concerts in the CHAR, but omitted this information in the CER, while 6.1% expressed attending concerts in the CER and then omitted this information from the CHAR.

Criterion validity

The score obtained in the CHAR questionnaire was a significant predictor for the presence of notch in the 4 kHz frequency of the right ear (odds ratio [OR]: 1.093, CI 95%: 1.025-1.167). For every point increase in the questionnaire, the odds of presenting a notch in the 4 kHz frequency in the right ear increased by 9.39%. The adjustment criterion of Hosmer-Lemeshow showed that the model was well adjusted (P = 0.078).

In the 4 kHz frequency in the left ear, scores were not found to be a significant predictor (OR: 1.016, CI 95%: 0.967-1.068). Neither was a new score found to be associated with the presence of notch in the 6 kHz frequency in the right ear (OR: 1.022, CI 95%: 0.966-1.082).

Regarding the presence of notch in the 6 kHz frequency in the left ear, the score obtained in the CHAR was a significant predictor (OR: 1.003-1.059). For each increased point in the questionnaire, the odds of presenting a notch in the 6 kHz frequency in the left ear increases by 3.07%. The adjustment criterion of Hosmer-Lemeshow showed that the model was well adjusted (P = 0.515).

The questions that were found to be associated with the presence of notch in 4 kHz in the right ear were numbers 6 and 7. For question 6, for every additional point in this (decreased perception of external sounds when using a portable music player), the possibility of the presence of notch in 4 kHz in the right ear increased 1.85 times (OR: 1.13-3.03). In the case of question 7, for every additional point in this (increase years of using a portable music player), the possibility of the presence of notch in 4 kHz in the right ear increased 2.35 times (1.23-4.47). The Hosmer-Lemeshow adjustment criterion test showed that both models were well-adjusted (P = 0.801 and P = 0.873, respectively).

Reliability

[Table 5] shows Cronbach's alpha values for each question and item. These values, in the case of item 2 and 3, differed from those calculated by the formula proposed by Raykov [16] based on the confirmatory analysis of factors.
Table 5: Cronbach's alpha and reliability of the CHAR according to Raykov

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  Discussion Top


A CHAR questionnaire was drawn up and validated in a sample of 335 Chilean university students. The purpose of the instrument is to determine the listening habits of young students and thus, the level of exposure to recreational noise. Its application could detect, at an early stage, those subjects with auditory behaviors that pose a higher risk for presentation of noise-induced hearing loss.

Regarding the questionnaire's validation process, the judges expressed their agreement on the essential character of 16 questions, which acknowledge many of the most widespread contexts among young people of recreational noise exposure, suggesting a strong validity of content. We included questions related to the type and frequency of use of varied types of portable music players. These devices have experienced a massive growth, accounting for a global phenomenon. [25] The wake-up call in terms of noise exposure is related to the fact that these devices reach over 120 dB with their controls at maximum intensity. [26] Exposure to noise through the use of portable players has been favored due to the increased functionality of mobile phones, which in large percentages include the ability to play audio tracks; [27] so they were also included in the questionnaire. This is particularly significant for a country like Chile, where it is estimated that there are nearly 24 million active mobile phones, reaching 1.38 phones per capita. [28] In turn, questions were selected concerning the contexts of use, where the choices included within the subway which, as measured in Chile by Platzer et al. constitutes the noisiest method of public transport. [29] Finally, the panel included questions related to attending concerts and other noisy venues such as pubs and discotheques, where there have been measurements of 105 dB, 96 dB and 106 dB, which are clearly harmful to hearing. [12]

Exploratory analysis of factors showed that the CHAR questions were grouped in three-dimensions:

  1. Use of portable music players;
  2. Concert attendance; and
  3. Attendance to other noisy venues.


These factors explained a large percentage of the variability of the scores of the instrument which account for a good construct validity. The factorial structure was confirmed with excellent indices of adjustment of the proposed model. Furthermore, the factorial charges of the confirmatory analysis were greater than 0.4, which means that each question is a strong indicator of the latent factors. The confirmatory analysis helped identifying questions that were related for reasons unrelated to the factorial structure, and then to clear error covariance associated with these, enabling the improvement of the adjustment criterion.

The existence of differences in the questions' format and content between CHAR and CER questionnaires, as expected, found correlations that showed to be higher when considering questions consulted for similar conduct (type and frequency of use of certain portable music players). Regarding the agreement between both questionnaires, as proposed by Altman, [30] this could be considered good as in the case of reported use of music playback devices, moderate in relation to attendance at other noisy, and poor when contacted about attending concerts. These differences may be due to the fact that in the CHAR, the attendance options were more open: Once a month, less than 3 times a year, occasionally, etc., unlike the output indicated in the CER, where attendance is used to indicate weekly attendance. This influenced the low percentage of subjects who reported attending concerts in the CER questionnaire (4.92%). This could mean that previous research using the CER underestimated attendance at one of the environments with higher noise exposure level.

As for the validity criterion of the obtained score, it was a significant predictor for the presence of notch in the 6 kHz frequency of the left ear and the 4 kHz frequency of the right. The CHAR could be used as a tool to identify those young people who are exposed to high noise levels in recreational activities at an early stage. They may experience noise-induced hearing loss from an early age.

Cronbach's alpha questionnaire's reliability was greater than 0.75 for all questions, indicating a good internal consistency of the instrument. Incorporating the results of the confirmatory factor analysis in the formula proposed by Raykov, yielded an alpha greater than 0.8. In this case, since this formula was not applied and there were no errors of covariance in the second and third factor, the actual reliability of the questionnaire was underestimated.

Since there are tools such as confirmatory factor analysis, this questionnaire can also become an interesting application for other age ranges (schools and/or active working adult population), evaluating the way the factors identified behave.


  Acknowledgments Top


The authors of the present investigation are grateful for the constant contributions from both Dr. Paulina Pino, associate professor from the Department of Epidemiology, School of Public Health of University of Chile, and Dr. Josiane Bonnefoy, assistant professor from the Department of Health Policies and Management, School of Public Health of University of Chile.

 
  References Top

1.Rabinowitz PM. Noise-induced hearing loss. Am Fam Physician 2000;61:2749-56, 2759.  Back to cited text no. 1
[PUBMED]    
2.Rabinowitz PM. The public health significance of noise-induced hearing loss. In: Le Prell CG, Henderson D, Fay RR, Popper AN, editors. Noise-Induced Hearing Loss: Scientific Advances. 1 st ed. LLC: Springer; 2012. p. 13-25.  Back to cited text no. 2
    
3.Niskar AS, Kieszak SM, Holmes AE, Esteban E, Rubin C, Brody DJ. Estimated prevalence of noise-induced hearing threshold shifts among children 6 to 19 years of age: The Third National Health and Nutrition Examination Survey, 1988-1994, United States. Pediatrics 2001;108:40-3.  Back to cited text no. 3
    
4.Rabinowitz PM, Slade MD, Galusha D, Dixon-Ernst C, Cullen MR. Trends in the prevalence of hearing loss among young adults entering an industrial workforce 1985 to 2004. Ear Hear 2006;27:369-75.  Back to cited text no. 4
    
5.Shargorodsky J, Curhan SG, Curhan GC, Eavey R. Change in prevalence of hearing loss in US adolescents. JAMA 2010;304:772-8.  Back to cited text no. 5
    
6.Henderson E, Testa MA, Hartnick C. Prevalence of noise-induced hearing-threshold shifts and hearing loss among US youths. Pediatrics 2011;127:e39-46.  Back to cited text no. 6
    
7.Jofré D, de La Paz F, Platzer L, Anabalón JL, Grasset E, Barnafin N. Assessment of social noise exposure in Chilean youth. Rev Otorrinolaringol Cir Cabeza Cuello 2009;69:23-8.  Back to cited text no. 7
    
8.Zenker F, Altahona MP, Barajas JJ. Adolescents′ noise exposure due to leisure activities. Rev Logop Fon Adiol 2001;21:173-80.  Back to cited text no. 8
    
9.Breinbauer HA, Anabalon JL, Gutiérrez D, Caro J. Personal music player usage habits and risks in a Chilean population sample. Rev Otorrinolaringol Cir Cabeza Cuello 2011;71:31-8.  Back to cited text no. 9
    
10.Beach E, Williams W, Gilliver M. Estimating young Australian adults′ risk of hearing damage from selected leisure activities. Ear Hear 2013;34:75-82.  Back to cited text no. 10
    
11.Lawshe CH. A quantitative approach to content validity. Pers Psychol 1975;28:563-75.  Back to cited text no. 11
    
12.Wang J, Wang X. Structural Equation Modeling Applications Using Mplus. 1 st ed. New York: John Wiley & Sons, Inc; 2012.  Back to cited text no. 12
    
13.International Organization of Standardization. Acoustics. Audiometric test Methods-Part 1: Basic pure tone air and bone conduction threshold audiometry. Geneva: ISO; 1989.  Back to cited text no. 13
    
14.Osei-Lah V, Yeoh LH. High frequency audiometric notch: An outpatient clinic survey. Int J Audiol 2010;49:95-8.  Back to cited text no. 14
    
15.Coles RR, Lutman ME, Buffin JT. Guidelines on the diagnosis of noise-induced hearing loss for medicolegal purposes. Clin Otolaryngol Allied Sci 2000;25:264-73.  Back to cited text no. 15
    
16.Raykov T. Behavioral scale reliability and measurement invariance evaluation using latent variable modeling. Behav Ther 2004;35:299-331.  Back to cited text no. 16
    
17.Bernstein IH, Teng G. Factoring items and factoring scales are different: Spurious evidence for multidimensionality due to item categorization. Psychol Bull 1989;105:467-77.  Back to cited text no. 17
    
18.Hutcheson G, Sofroniou N. The Multivariate Social Scientist: Introductory Statistics Using Generalized Linear Models. 1 st ed. London: SAGE; 1999.  Back to cited text no. 18
    
19.Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Modeling 1999;6:1-55.  Back to cited text no. 19
    
20.Bentler PM, Bonett DG. Significance test and goodness of fit in the analysis of covariance structures. Psychol Bull 1980;88:588-606.  Back to cited text no. 20
    
21.MacCallum RC, Browne MW, Sugawara HM. Power analysis and determination of simple size for covariance structure modeling. Psychol Methods 1996;1:130-49.  Back to cited text no. 21
    
22.Byrne BM. Structural Equation Modeling with Lisrel, Prelis, and Simplis: Basic Concepts, Applications, and Programming. New Jersey: Lawrence Erlbaum Associates, Inc; 1998.  Back to cited text no. 22
    
23.Byrne BM. Structural Equation Modeling with Mplus: Basic Concepts, Applications, and Programming. New York: Routledge, Taylor and Francis Group; 2012.  Back to cited text no. 23
    
24.Brown TA, Moore MT. Confirmatory Factor Analysis. In: Hoyle RH, editor. Handbook of Structural Equation Modeling. New York: The Guilford Press; 2012.  Back to cited text no. 24
    
25.Breinbauer HA, Anabalón JL, Gutierrez D, Cárcamo R, Olivares C, Caro J. Output capabilities of personal music players and assessment of preferred listening levels of test subjects: outlining recommendations for preventing music-induced hearing loss. Laryngoscope 2012;122:2549-56.  Back to cited text no. 25
    
26.Fligor BJ, Cox LC. Output levels of commercially available portable compact disc players and the potential risk to hearing. Ear Hear 2004;25:513-27.  Back to cited text no. 26
    
27.SCENIHR (Scientific Committee on Emerging and Newly-Identified Health Risks). Scientific opinion on the potential health risks of exposure to noise from personal music players and mobile phones including a music playing function. September 23, 2008. Available from: http://www.ec.europa.eu/health/opinions/en/hearing-loss-personal-music-player-mp3 [Last accessed on October 29, 2013.  Back to cited text no. 27
    
28.Subsecretiarat of Telecommunications. Transport and Telecommunications Ministry. Sectorial report: Telecommunications in Chile. Figures as of December 2012  Back to cited text no. 28
    
29.Platzer L, Iniguez R, Cevo J, Ayala F. Environmental noise levels measurement of the city of Santiago, Chile. Rev Otorrinolaringol Cir Cabeza Cuello 2007;67:122-8.  Back to cited text no. 29
    
30.Altman DG. Practical Statistics for Medical Research. London: Chapman and Hall; 1991.  Back to cited text no. 30
    

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Correspondence Address:
Prof. Eduardo A Fuentes López
Facultad de Medicina, UDA Ciencias de la Salud, Carrera de Fonoaudiología, Pontificia Universidad Católica de Chile. Avenida Vicuña Mackenna 4860, Macul, Santiago
Chile
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1463-1741.140509

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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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