AJSLP

Research Note

Accuracy of Self-Reported Estimates

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of Daily Voice Use in Adults With Normand Disordered Voices

Daryush D. Mehta,a,b,c Harold A. Cheyne II,d Asa Wehner,a

James T. Heaton,a,b,c and Robert E. Hillmana,b,c

rpose: Accurate estimation of daily patterns of vocalhavior is essential to understanding the role of voice usevoice disorders. Given that clinicians currently rely on

hislts wnt o

embe usionNJ)rovidl anaetw

self-reported and APM-based estimates of phonation timerevealed subject- and group-specific characteristics.Results: A majority of subjects exhibited a significant bias

nentsfnt to

telya

ngvoice

t fo ts to

patient self-report to assess daily vocal behaviors, tstudy sought to assess the accuracy with which aduand without voice disorders can estimate their amoudaily voice use in terms of phonation time.Method: Eighteen subjects (6 patients, 6 matched mof a control group without voice disorders, 6 low voicwore the accelerometer-based Ambulatory PhonatMonitor (APM; model 3200, KayPENTAX, Montvale,at least 5 workdays. Subjects were instructed to phourly self-reports of time spent talking using a visuascale. Spearman correlation coefficients and errors b

ccurate estimation of voice use is importan

oiceatetipleamend tovocTitz

enter for Laryngeal Surgery and Voice Rehabilitation,ssachusetts General Hospital, Bostonarvard Medical School, Boston, MAstitute of Health Professions, Massachusetts General Hospital,stonioacoustic Research Program, Lab of Ornithology, Cornelliversity, Ithaca, NY

rrespondence to Daryush D. Mehta: daryush.mehta@alum.mit.

itor: Krista Wilkinsonsociate Editor: Preeti Sivasankar

ceived July 20, 2015vision received January 27, 2016cepted April 18, 2016I: 10.1044/2016_AJSLP-15-0105

American Journal of Speech-Language Pathology • Vol. 25 • 634–64

ithf

ersers)

forelogeen

toward overestimating their phonation times, with aaverage absolute error of 113%. Correlation coefficibetween self-reported and APM-based estimates ophonation time ranged from statistically nonsignifica.91, reflecting large intersubject variability.Conclusions: Subjects in all 3 groups were moderaaccurate at estimating their hourly voice use, withconsistent bias toward overestimation. The resultssupport the potential role that ambulatory monitoricould play in improving the clinical assessment ofdisorders.

r Švec, & Popolo, 2003). There have also been effor

atory times distrib-

understanding its role in the developmen

in attaining a better

t ofvoice disorders, especially for professions requir-

quantify how the durations of nonphonute across entire days and longer, to beg

” ins (Titze,

mpactthroughas theman,997)wever,ized

Aing substantial voice use (Vilkman, 2004). Several vuse-related measures have been developed to estimambulatory vocal function over the course of muldays. Traditional measures of sound intensity, fundfrequency, and phonation time have been proposeyield daily phonation profiles, along with cumulativedose measures such as cycle dose and distance dose (

ability. Onrede evenheirrenesst of a

-

tal

al-e,

understanding of the potential role of “recovery timemitigating the occurrence of common voice disorderHunter, & Švec, 2007).

Clinicians can obtain information about the iof voice disorders on the daily function of patientsthe use of standardized self-report inventories suchVoice-Related Quality of Life (Hogikyan & Sethura1999) and Voice Handicap Index (Jacobson et al., 1assessments. Actual estimates of typical voice use, hoare still usually obtained as part of the nonstandardclinical interview process, and the validity and reliof such highly subjective estimates is questionablethe basis of our clinical experience, we also wondewhether some patients with voice disorders may bless reliable than normal speakers in self-reporting tvoice use because of reduced self-monitoring or awathat could conceivably contribute to the developmen

edu

Disclosure: Robert E. Hillman has a financial interest in the Ambulatory PhonationMonitor (APM) based on a contractual agreement between Sensimetrics, Inc. (R & Dfor the initial version of the APM) and KayPENTAX, Inc. (manufacturer of theAPM).

41 • November 2016 • Copyright © 2016 American Speech-Language-Hearing Association

voice-use-related disorder. This is somewhat supported byanecdotal observations indicating that psychosocial factorsmay play a larger role in self-reports by people with voice

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anteffic“voile dorvedto ovy, al-tatistt stuscrep%) abaseoweanded acent(201Loger coatessubjeencetimes.ntedestigationulatousticilent al.arbeambphoatana2001u, &n,atonFen005kinctiv09).techas btannicalng evn thaThethe c

The purpose of the current study was to assess the ac-curacy of self-reports of voice use by comparing individuals’estimates of their speaking times with measures of phona-

ulatoryitiall-folddifferede-useupa-g time.esti-nationllengingn con-m withe.insightassoci-bouthe pres-clinicalment

Subject Characteristicstientpa-

odulesachvoiceme sexe ast andndoingumatictial—wasditionalstafftoryp alsoocolt differ-p andntialscopicandce (invoiceandthee and

e 635

disorders than those without (Watanabe, Shin, Oda, F& Komiyama, 1987).

In a group of 12 teachers with normal voices, Rand Vilkman (1999) found a moderate correlation coof .66 between self-reported ratings of nonspecificcomplaints” and an acoustic-based measure of cycBuekers, Bierens, Kingma, and Marres (1995) obsehowever, that speakers with normal voices tendedestimate acoustic-derived measures of vocal intensitthough no details regarding specific rating scales or sevidence were given. Of direct relevance to the currenOhlsson, Brink, and Löfqvist (1989) reported large diancies between self-reported speaking time (62%–71phonation time derived from a contact-microphone-ambulatory voice monitor (5%–7%); in that study, honly speakers with normal voices were monitored,quantitative statistical analysis between self-reportvoice-monitor data was not carried out. In more rework, Misono, Banks, Gaillard, Goding, and Yuehreport that phonation times measured with a Voca(Griffin Laboratories, Temecula, CA) voice dosimetrelated moderately (r = .62) with self-reported estimvoice use by subjects with normal voices. However,were monitored for only 2 hr, and there is some evidthat the VocaLog tends to overestimate phonation(Van Stan, Gustafsson, Schalling, & Hillman, 2014)

As noted in several studies, caution is warrawhen comparing results from different voice-use invtions to distinguish between speaking time and phontime. Speaking time is typically estimated with ambmonitors that use microphones to capture the acospeech signal that includes voiced, unvoiced, and ssegments (Airo, Olkinuora, & Sala, 2000; Buekers e1995; Sala et al., 2002; Södersten, Granqvist, Hamm& Szabo, 2002). Phonation time has been studied inlatory settings using both neck-placed contact micro(Ohlsson et al., 1989; Ryu, Komiyama, Kannae, & W1983; Szabo, Hammarberg, Håkansson, & Södersten,Watanabe et al., 1987; Watanabe, Komiyama, RyKannae, 1984) and accelerometers (Cheyne, HansoGenereux, Stevens, & Hillman, 2003; Hillman, HeMasaki, Zeitels, & Cheyne, 2006; Mehta, Zañartu,Cheyne, & Hillman, 2012; Popolo, Švec, & Titze, 2Titze et al., 2007) that respond primarily to neck svibration generated during phonation, with little aduring unvoiced speech sounds (Zañartu et al., 20

It should also be noted that, even though thenology for objective voice ambulatory monitoring hcome commercially available in recent years (Van Set al., 2014), it has not been adopted for routine cliuse. This is at least partly due to a lack of compellidence that such monitoring can provide informatiocould improve the clinical voice-evaluation process.need for such evidence was a major motivation forrent study.

ura,

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icaldy,-nddver,and

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tion time derived from an accelerometer-based ambphonation monitor. We also sought to attain an insense of whether individuals with and without vocapathologies working in high-voice-use occupationsfrom each other in the accuracy of their self-reportspeaking time and whether individuals in low-voicoccupations differ from those in high-voice-use occtions in the accuracy of their self-reported speakinIn the current study, subjects were simply asked tomate their speaking time, because voicing and photime were considered too conceptually abstract or chato directly estimate. Speaking-time estimates were theverted to estimates of phonation time to compare thethe accelerometer-based estimates of phonation tim

The results of this study should provide betterinto whether subjective self-reporting of voice use isated with sufficient error to affect clinical decisions athe role of voice use in common voice disorders. Tence of such error would also lend support for theuse of ambulatory monitoring to improve the assessof voice use.

Method

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Table 1 reports subject characteristics. The pagroup comprised six individuals who had vocal-foldthology associated with phonotrauma (vocal-fold nor polyps) before any treatment was administered. Epatient was in an occupation requiring substantialuse and was asked to identify a colleague of the sain the same profession and as close to the same agpossible to serve as a matched control-group subjecyield a control group of six subjects. The patient acontrol data were gathered as part of a larger ongproject addressing the role of voice use in phonotravoice disorders, where this type of matching is essenonly this subset of that much larger subject groupasked to self-assess their amount of voice use. An adsix subjects were recruited from laboratory researchto comprise a low-voice-use group. Because ambulavoice monitoring was still relatively new, this grouserved as an overall reality check for the study protand monitoring process (i.e., the lack of a significanence in measured phonation times between this grouthe groups of heavy voice users would signal a poteproblem). All subjects underwent a laryngeal endoexamination by an experienced team (laryngologistspeech-language pathologist) to confirm the presenpatients) or absence (in the control group and lowusers) of vocal-fold nodules prior to participationgroup assignment. This study was preapproved byInstitutional Review Board of the Massachusetts EyEar Infirmary.

Mehta et al.: Accuracy of Self-Reported Voice Us

Data CollectionEach subject wore an Ambulatory Phonation Monitor

for an ofwlesf th

neck using a medical-grade adhesive (Skin-Bond, Smith& Nephew, London, United Kingdom; or model B-401,Factor II, Inc., Lakeside, AZ) just above the sternal notch

tructedmoni-ion, thee sub-e wasationre level

Table 1. Subject identifier, age (in years), and occupation of subjects in the patient, control, and low-voice-user groups, with patientdiagnoses.

Sex Patient Control Low Voice User

F P1, 37, Nodules, Teacher C1, 49, TeacherF P2, 22, Nodules, Salesperson C2, 23, SalespersonF P3, 46, Nodules, Clinician C3, 52, Clinician LVU3, 52, Researcher (Histologist)F P4, 54, Nodules, Teacher C4, 62, Teacher LVU4, 59, Researcher (Histologist)M P5, 19, Polyp, Singer C5, 20, Singer LVU5, 29, Researcher (Engineer)F P6, 30, Nodules, Clinician C6, 26, Clinician LVU6, 29, Animal-care technicianM LVU1, 31, Researcher (Physiologist)M LVU2, 48, Researcher (Engineer)

Note. Subjects appearing in the same row were matched by sex and approximate age.

chmwire

(APM; model 3200, KayPENTAX, Montvale, NJ)least five workdays. Figure 1 illustrates the positioa miniature accelerometer (model BU-27135, KnoElectronics, Inc., Itasca, IL) attached to the front o

Figure 1. Photograph showing a typical accelerometer attalocation on the neck surface above the sternal notch, with

structedf theireportedrk oneft of. Innatureted toubjectsingre notiven theinderg scales(e.g.,tualbbott,we didgories

connection to the Ambulatory Phonation Monitor microprocessobox. The inset provides a magnified view of the accelerometer nto a U.S. penny for size comparison. Adapted from “AmbulatoryMonitoring of Daily Voice Use,” by R. E. Hillman and D. D. Meht2011, SIG 3 Perspectives on Voice and Voice Disorders, 21, p. 5Copyright 2011 by the American Speech-Language-HearingAssociation. Adapted with permission.

636 American Journal of Speech-Language Pathology • Vol.

t

e

to record neck-surface acceleration. Subjects were insnot to alter their typical vocal behavior while beingtored. At the beginning of each day of data collectsubject was fitted with the APM at the clinic or at thject’s place of work. An acoustic calibration routinperformed each morning to allow for the interpretof acceleration amplitude in terms of sound pressu(SPL; Cheyne et al., 2003).

After each hour of monitoring, subjects were into fill out a voice-use diary to keep a written record oactivities throughout their workday. Subjects self-rtheir “time spent talking” each hour by placing a maa visual analog scale ranging from None on the far lthe scale to Continually on the far right of the scaleaddition, the diary prompted subjects to specify theof the time they spent talking (percentage time devoface-to-face talking, talking to an audience, etc.). Swere, unfortunately, much less consistent in providresponses for these additional scales, so these data aincluded in the current research note. Subjects were goption of carrying a timer to provide an hourly remvia an audible beep or tactile vibration. Visual analowere chosen on the basis of the design and rationaleease of use) used in the Consensus Auditory-PercepEvaluation of Voice (Kempster, Gerratt, Verdolini ABarkmeier-Kraemer, & Hillman, 2009) and becausenot have any basis for determining how many subcateor divisions to include in a numerical scale.

Data Analysis

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The APM performed online processing of the acceler-entalvoicingme intoues ofold,rames,L toy the

ometer signal to yield estimates of SPL and fundamfrequency (f0) every 125 ms (Cheyne et al., 2003). Adecision was made by first dividing each 125-ms frafive 25-ms subintervals. If the root-mean-square valtwo contiguous subintervals exceeded a preset threshthe entire frame was considered voiced. For voiced fSPL was estimated by a linear function relating SPaccelerometer root-mean-square level determined b

25 • 634–641 • November 2016

acoustic calibration routine. An estimate of f0 was computedfrom the largest peak in the autocorrelation function of the125-ms frame. For unvoiced frames, SPL and f0 values

acedPL hbe in thlicaareX,thatm nolsivetivetimeo allasure

g wer spength% ajectsercea makinsistsicedd, 19entagstimn timrtedtistice levourperced anedetri

ibutirwistweecross

1 anletinividuy anveryeir dary trepond d

of recording, once they had become accustomed to makingdiary entries each hour. Due to compliance issues andintermittent technical difficulties, three subjects (P6, C4,

withsubjectse not

f thechficantrsub-ovariedowardjectsa statis-ey didse. Thethanicallye theirr oner voicengesated byterms7% to

atientsantlyandin thosethanw voicetheirects,ntageshouldmple

self-pondingubjectine,s oftenon-t C1 is

bulatoryracystimatever theupsce-useatchede; and

e 637

were set to 0.Additional postprocessing constraints were pl

prior to storing the parameters of a voiced frame: Sto be in the range of 50–130 dB SPL, and f0 had tothe range of 70–400 Hz. These limits were chosen obasis of parameter ranges used in the commercial appof the APM and a widely used pitch-tracking softwprogram (Computerized Speech Lab, KayPENTAMontvale, NJ). The limits sought to avoid framesincluded spurious values that may have resulted frovocal activity (e.g., intense ambient noise and impumechanical motion of the accelerometer) or vegetasounds (e.g., laughing and coughing). The startingdex for each frame was saved in the APM data file tfor synchronized comparisons between objective meof vocal behavior and voice-use-diary information.

Only the hourly estimates of time spent talkinused in this study. Marks on the self-report scale foing time were converted to a percentage of the line lewith marks on the far left of the scale representing 0marks on the far right representing 100%. Some subchose to report their speaking time each hour as a page written above the visual analog scale instead ofon the scale; this practice was allowed. Because spetime (termed talking time in the voice-use diary) conof approximately 50% voiced speech and 50% unvospeech and silent periods (Fant, Kruckenberg, & NorLöfqvist & Mandersson, 1987), the self-reported percwere divided by a factor of 2 to yield phonation-time ethat could be compared with APM-derived phonatio

Biases (average differences) between self-repoand APM-based phonation time were tested for stasignificance using paired t tests at a 95% significancSelf-reported and APM-based phonation time per hwere converted to minutes per hour by multiplyingphonation by 60 min. Covariance between self-reportAPM-based estimates of phonation time was examiusing Spearman correlation coefficients for nonparamdata because of the non-Gaussian nature of the distrof hourly phonation times. Tests for statistical paidifferences were performed within each subject, besubject groups, and over all subject data pooled aall hourly data points.

ResultsTotal monitoring durations varied between 2

92 hr per subject. Compliance of subjects in comptheir voice-use diary entries also varied. Some indwrote in detail about their activities during the dafaithfully reported an estimate of their talking time ehour. In contrast, other individuals were sparse in thscriptions and sometimes filled out their voice-use difollowing day. Subjects who wore the reminder timerthat they tended not to use it after their first or seco

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LVU2) yielded only 21–23 hr of APM monitoringcorresponding self-report data. The remaining 15provided over 30 hr of data. Partial-hour data werincluded.

Table 2 provides a comprehensive reporting oability of subjects to estimate their own voice use eahour. Correlation coefficients ranged from nonsigni(P1, P2, C1, C4) to .91 (LVU5), reflecting large inteject variability in the extent to which the measures cwithin subjects. The Bias column reflects any bias tover- or underestimation of phonation time. Six sub(P2, P3, C2, LVU1, LVU2, LVU5) did not exhibittically significant self-report bias, indicating that thnot consistently under- or overestimate their voice uexplained variance, however, was still typically less50% for these subjects. All individuals with a statistsignificant bias (11 subjects) tended to overestimatvoice use (positive values of average bias), except fo(C1) who appeared to consistently underestimate heuse. For these individuals, average absolute error rafrom 3.2 to 11.0 min/hr, with large variability indicstandard deviations of the absolute error values. Inof percentages, the absolute error ranges from 49.258.6%.

Group-based statistics in Table 2 show that pand subjects in the control group were not significdifferent from each other in terms of self-reportedAPM-based phonation time. As expected, subjectstwo groups exhibited significantly higher voice usesubjects assigned to the low-voice-use group; the lousers also reported significantly lower estimates ofphonation time. Pooling hourly data across all subjthe overall absolute error is 113.3% ± 142.0 percepoints (5.7 ± 5.0 min). These group-based resultsbe viewed as somewhat tentative given the small sasizes.

Figure 2 displays the raw hourly data for thereported phonation times plotted against the corresAPM-based phonation times for each of the three sgroups. Most data points lie above the unity-slope lreflecting the fact that individuals in all three grouptended to overestimate their phonation times. The csistent underestimation of phonation time by subjecvisible in Figure 2A.

DiscussionThe goal of this study was to use improved am

voice-monitoring technology to determine the accuwith which three different groups of subjects could etheir amount of hourly voice use (phonation time) ocourse of a regular 5-day workweek. The three growere patients with laryngeal pathologies in high-voioccupations; subjects with normal voices who were mto the patients according to occupation, sex, and ag

Mehta et al.: Accuracy of Self-Reported Voice Us

subjects with normal voices whose occupations required lessvoice use compared to the other groups.

There was a range of compliance associated withrly ht migestiusinthecomwing

al tir cour pa4–Pationut aisk foan,

e av/hr,.0%.ues orted(19

byako

patie

with nodules); and Titze et al. (2007; 23% for teachersduring the workday).

Valid assessment of whether individuals were accurateectedPM,some-mparingonation2006).r signalyzinghe sub-munences.ross allding7%.ore

eir con-jects,atientxhibitedutesificantlytermsort pho-reover,groups

Table 2. Accuracy of voice-use estimation for each subject and subject group.

Subject IDDuration

(hr)Self-report

(min)APM(min)

Correlation(ρ)

Bias(min)

Bias(%)

Absolute error(min)

Absolute error(%)

P1 37 21.9 (6.8) 16.5 (5.1) n.s. 5.4 (7.2) 50.4 (94.9) 7.1 (5.5) 59.8 (89.0)P2 34 9.9 (6.7) 7.6 (3.0) n.s. n.s. n.s. n.s. n.s.P3 40 10.5 (5.8) 9.9 (4.6) .58 n.s. n.s. n.s. n.s.P4 40 18.2 (9.8) 11.6 (6.2) .64 6.6 (7.6) 95.7 (126.3) 8.2 (5.8) 106.5 (117.1)P5 40 4.9 (5.4) 2.9 (3.4) .60 2.0 (4.7) 27.8 (177.0) 3.4 (3.7) 129.3 (122.2)P6 23 17.8 (6.9) 10.5 (5.6) .58 7.3 (5.6) 106.6 (111.3) 7.6 (5.1) 109.9 (108.0)P group 214 13.5b (9.2) 9.8b (6.3) .69 3.8b (6.6) 52.9a,b (120.2) 5.7a,b (5.1) 85.9a,b (99.3)C1 37 11.3 (6.9) 17.0 (6.2) n.s. −5.7 (8.3) −26.1 (48.4) 8.7 (4.9) 49.7 (22.5)C2 40 9.8 (6.4) 9.0 (7.5) .68 n.s. n.s. n.s. n.s.C3 40 18.5 (8.7) 8.4 (4.6) .45 10.1 (7.7) 171.1 (191.9) 11.0 (6.4) 181.4 (182.0)C4 21 23.9 (5.3) 16.1 (6.6) n.s. 7.7 (7.4) 84.7 (121.0) 9.1 (5.6) 91.0 (116.1)C5 40 13.5 (6.0) 4.5 (3.1) .60 9.0 (5.0) 242.8 (212.4) 9.1 (4.9) 258.6 (192.3)C6 32 9.3 (6.4) 6.7 (5.2) .45 2.6 (6.3) 96.1 (148.4) 5.3 (4.2) 121.1 (128.1)C group 210 13.8c (8.2) 9.8c (7.2) .41 4.0c (8.7) 105.6a (183.5) 7.7a,c (5.6) 133.4a (164.3)LVU1 30 5.5 (6.0) 5.9 (5.6) .74 n.s. n.s. n.s. n.s.LVU2 21 6.9 (3.0) 7.4 (3.6) .55 n.s. n.s. n.s. n.s.LVU3 40 7.5 (3.9) 3.8 (3.0) .48 3.7 (2.6) 153.9 (178.4) 3.9 (2.3) 159.2 (173.6)LVU4 40 6.9 (3.7) 5.0 (2.8) .46 1.8 (3.7) 80.6 (175.0) 3.2 (2.6) 98.9 (165.1)LVU5 40 6.4 (7.7) 5.9 (7.8) .91 n.s. n.s. n.s. n.s.LVU6 36 13.5 (4.0) 5.6 (3.2) .54 7.9 (3.9) 197.8 (143.9) 8.0 (3.6) 198.5 (142.9)LVU group 207 7.8b,c (5.7) 5.4b,c (4.8) .62 2.4b,c (4.4) 97.0b (167.6) 3.8b,c (3.3) 121.2b (150.9)All subjects 631 11.8 (8.3) 8.4 (6.5) .63 3.4 (6.8) 85.0 (160.6) 5.7 (5.0) 113.3 (142.0)

Note. Self-report and Ambulatory Phonation Monitor (APM) display mean (standard deviation [SD]) of self-reported (half of the judgment of talkingtime) and APM-based measures, respectively, of phonation time over the number of hours listed under Duration. Spearman rho correlation iscomputed for self-reported and APM-based phonation time (n.s. = not significant, p ≥ .05). Bias quantifies mean (SD) of hourly estimation errorby subtracting APM-based phonation time from half of the self-reported talking time, where the hourly error magnitude is used for computingthe absolute error mean (SD). Boldface rows report mean (SD) after pooling all hourly data from patient (P), control (C), and low-voice-user(LVU) groups. Groups exhibiting statistically significant pairwise differences are marked by the same symbol: P–C (a ), P–LVU (b ), C–LVU (c ).

Vol.

the task of self-reporting voice use that could cleaaffected the accuracy of these estimates. Although ibe possible to improve the accuracy of self-reportedmates by facilitating better task compliance (e.g.,additional incentives), it could also be argued thatobserved variation mimics the type of variability inance that different patients typically display in folloinstructions related to their clinical care.

As expected, the low voice users spent less totphonating per hour than did subjects in the patient otrol groups (Table 2). It is unsurprising that the foof teachers in the study (subject pairs C1–P1 and Cexhibited some of the highest average hourly phontimes. As a profession, teachers have been singled ogroup requiring extra care because of their higher rdeveloping voice disorders (Roy et al., 2004; Vilkm2004). Pooling data across all subjects (631 hr), thage APM-based phonation time was 8.4 ± 6.5 mincorresponding to an average phonation time of 14This value is comparable to other APM-based valphonation time for adults with normal voices repoby Watanabe et al. (1987; 11%) and Ohlsson et al.8.6%) but less than the phonation times reportedWatanabe et al. (1984; 20%); Masuda, Ikeda, Manand Komiyama (1993; 21% for teachers, 22% for

638 American Journal of Speech-Language Pathology •

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in their self-reported voice use could obviously be affby how well phonation time was measured by the Aparticularly for disordered voices. This concern waswhat mitigated by the results of our previous work comicrophone- and accelerometer-based estimates of phtime in normal and disordered voices (Hillman et al.,That study provided evidence that the accelerometewas more robust than the microphone signal for analseverely disordered voices, which was attributed to tglottal location of the accelerometer being largely imto turbulent noise generation and vocal-tract resona

The average self-reported phonation time acsubjects was 11.8 ± 8.3 min/hr (Table 2), corresponto an average hourly percent phonation time of 19.Overall, individuals in the patient group tended to maccurately estimate their speaking times than did thtrol cohort, although the errors are large for all subwhich casts doubt on the clinical validity of using pself-reporting to assess voice use. Low voice users ethe lowest absolute error (3.8 ± 3.3) in terms of minper hour. Their estimation error, however, was signgreater than that of patients when error was put inof percentages, probably owing to the inherently shnation times that the low voice users exhibited. Moalthough it is unknown to what degree the various

25 • 634–641 • November 2016

followed instructions to complete the voice-use diary eachhour of the day, the laboratory personnel comprising thelow-voice-use group might have been more diligent in this

roupontrimatight

diffehatd ovhoubilitdayd on. Evratetantdil

lls inrtingaren

of their voice use. A distinct advantage of newer phonationmonitors with a graphical user interface, such as the devicesin the studies by Popolo et al. (2005) and Mehta et al. (2012),

se orng onorting.foundct onveragemin)tionelds aphona-entindivid-timelf ofbly bes aboutt of, evenmost

Figure 2. Scatter plots of self-reported phonation time versus Ambulatory Phonation Monitor (APM)–based phonation time, in minutes per 1-hrperiod. Dashed lines indicate perfect accuracy. Numbered points refer to subject identifiers in Table 1 for subjects in the (A) control group,(B) low-voice-user group, and (C) patient group.

e 639

task due to their scientific training. And last, as a gthe patients were no worse than the subjects in the cgroup in terms of the accuracy of their voice-use estwhich is counter to the expectation that patients mperform more poorly at this task.

Because the method of reporting voice use isent in this study (voice use rated every hour) from wclinicians typically ask their patients (voice use ratedays), the result that individuals overestimated theirspeaking time might not hold for determining their ato estimate their speaking time throughout an entirealthough it is expected that estimates that are baselonger periods of time would be even less accuratethough study subjects were encouraged to be accuin their voice-use-diary entries, there was still subsvariability within and among subjects regarding howgently they completed their voice-use diaries. This caquestion the extent to which inaccuracies in self-repowere due to reporting inconsistencies or to poor aw

,oles,

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en

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ess

is the capability to query the user about their voice uenvironment on a preset schedule rather than relyisubject compliance for periodic paper-and-pencil rep

Typical overestimation of voice use that wasin the current study has a potentially broader impaclinical voice assessment. For example, adding the aabsolute error per hour for estimating voice use (5.7to the measured (APM monitoring) average phonatime per hour (8.4 min or 14% phonation time) yiself-report of 14.1 min/hr, which represents 23.5%tion time. In practical terms, converting these percphonation values into talk time (multiplying by 2),uals who are actually talking about a quarter of the(28%) could report that they are talking closer to hathe time (47%). Such discrepancies could conceivaof sufficient magnitude to influence clinical decisionthe role of voice use in the etiology and/or treatmencommon behavior-related voice disorders. Howeverthough the overall results of this study indicate that

Mehta et al.: Accuracy of Self-Reported Voice Us

individuals tend to significantly overestimate their voiceuse to varying degrees regardless of vocal status, this wasnot a universal finding, and the relatively small sample

niciathei

withpo

louds ofwhicthesis ofy probilit(e.g.,uensignibasedta, &15).its fotitatr tha015;

Hogikyan, N. D., & Sethuraman, G. (1999). Validation of an in-strument to measure voice-related quality of life (V-RQOL).Journal of Voice, 13, 557–569.

A.,997).lidation.6–70.kmeier-itory-dardizede Pathol-

.,5). Real-voicemerica,

pectrum–229.93).e andica, 113,

M.,015).mmonineering

I, &using aorm.0–3096.

size (18 subjects) precludes recommending that clisimply assume that all patients are overestimatingvoice use.

There are obviously other factors associatedvoice use in addition to phonation duration that cantially affect vocal health, including vocal intensity (ness) and fundamental frequency (pitch). The resultpresent study also cast doubt on the accuracy withpatients might be able to self-assess or self-monitorparameters during activities of daily living, whichrequired as part of the voice assessment and therapcess. Ambulatory voice monitors that have the capato objectively measure multiple vocal parametersphonation duration, intensity, and fundamental freqand provide real-time feedback have the potential tocantly improve the clinical management of behavior-voice disorders (Llico et al., 2015; Van Stan, MehHillman, 2015; Van Stan, Mehta, Zeitels, et al., 20This would include defining or establishing safe limhealthy voice use that are based on the types of quanor cumulative measures of daily phonatory behavioambulatory monitoring can provide (Mehta et al., 2Titze & Hunter, 2015).

Conclusions

The results of this study confirmed that people are

talk)atioidelyn tionitt.

ueh, B.ing voice

Speech

on of anal of.ubjectivechers’

S. D., &

generally inaccurate at estimating their phonation (time, exhibiting a consistent bias toward overestimof hourly voice use in a manner that correlates to wvarying degrees with objective measures of phonatioThis supports the potential that ambulatory voice ming may have in improving clinical voice assessmen

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