Natural Voice Use in Patients With Voice Disorders and Vocally Healthy Speakers Based on 2 Days Voice Accumulator Information From a Database

Natural Voice Use in Patients With Voice Disorders and Vocally Healthy Speakers Based on 2 Days Voice Accumulator Information From a Database ~o, *,†,§Anita McAllister, and ‡Sten Ternstro € dersten, *,‡Gl € m, *yzStockholm *,†Maria So aucia Laı´s Saloma and xLink€oping, Sweden

Summary: Objectives and Study Design. Information about how patients with voice disorders use their voices in natural communicative situations is scarce. Such long-term data have for the first time been uploaded to a central database from different hospitals in Sweden. The purpose was to investigate the potential use of a large set of long-term data for establishing reference values regarding voice use in natural situations. Methods. VoxLog (Sonvox AB, Ume a, Sweden) was tested for deployment in clinical practice by speech-language pathologists working at nine hospitals in Sweden. Files from 20 patients (16 females and 4 males) with functional, organic, or neurological voice disorders and 10 vocally healthy individuals (eight females and two males) were uploaded to a remote central database. All participants had vocally demanding occupations and had been monitored for more than 2 days. The total recording time was 681 hours and 50 minutes. Data on fundamental frequency (F0, Hz), phonation time (seconds and percentage), voice sound pressure level (SPL, dB), and background noise level (dB) were analyzed for each recorded day and compared between the 2 days. Variations across each day were measured using coefficients of variation. Results. Average F0, voice SPL, and especially the level of background noise varied considerably for all participants across each day. Average F0 and voice SPL were considerably higher than reference values from laboratory recordings. Conclusions. The use of a remote central database and strict protocols can accelerate data collection from larger groups of participants and contribute to establishing reference values regarding voice use in natural situations and from patients with voice disorders. Information about activities and voice symptoms would supplement the objective data and is recommended in future studies. Key Words: Voice accumulator–Accelerometer–Voice disorders–Voice SPL–Fundamental frequency–Phonation time–Vocal loading.

INTRODUCTION Little is known about how much people in general speak during a day, how fundamental frequency (F0) and voice sound pressure level (SPL) vary on a long-term basis, and how the level of background noise affects vocal behavior when speaking in everyday situations. Information about long-term voice use would be of value for identifying vocal loading factors for persons with vocally demanding occupations and for patients with voice disorders during vocal rehabilitation.1 Laboratory standard voice recordings are in general used to evaluate results of interventions, such as voice therapy, phonosurgery, or medical treatments, but may not be representative for the patients’ voice use outside the clinic.2–4 Recently, studies have been conducted collecting long-term voice data in natural settings. Most of those have focused on teachers5–10 and preschool teachers.4,11–15 A few have included singers,16 children,11

Accepted for publication September 4, 2014. From the *Division of Speech-Language Pathology, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden; yDepartment of Speech and Language Pathology, Karolinska University Hospital, Stockholm, Sweden; zDepartment of Speech, Music and Hearing, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden; and the xDepartment of Clinical and Experimental Medicine, Division of Speech and Language Pathology, Link€oping University, Link€ oping, Sweden. Address correspondence and reprint requests to Maria S€odersten, Department of Speech and Language Pathology, B69, Karolinska University Hospital, SE-141 86, Stockholm, Sweden. E-mail: [email protected] Journal of Voice, Vol. 29, No. 5, pp. 646.e11-646.e19 0892-1997/$36.00 Ó 2015 The Voice Foundation http://dx.doi.org/10.1016/j.jvoice.2014.09.006

and patients with voice disorders.17,18 Thus, we are in the beginning of building a basis of knowledge about how individuals with and without voice disorders use their voices in natural communicative situations. The largest long-term study, so far, was carried out by Hunter and Titze5 who documented the voice use of 57 teachers during 2 weeks using a voice dosimeter developed at the National Center for Voice and Speech. Each day, data were collected for 6 hours in an occupational setting and for 6 hours in a nonoccupational setting. An important finding was that phonation time per hour at work was more than twice that in the nonoccupational setting. The teachers spoke with approximately 2.5 dB higher SPL and 1–1.5 semitones higher F0 at work, as compared with the nonoccupational setting. The difference was larger for the female teachers than for the male teachers. The mean phonation time per hour during work was high, namely 29.9% (30.7% for female teachers and somewhat lower, 27.4%, for male teachers). Although the phonation time was lower in the nonoccupational setting, it was still rather high; 14.7% for female teachers and 13.7% for male teachers. Hunter and Titze5 discussed the potentially harmful impact from a vocally demanding nonoccupational setting on a voice already affected from work. Morrow and Connor7 compared voice use during work for music and classroom teachers and found that different teaching activities result in different amount of vocal loading. They used the Ambulatory Phonation Monitor (APM; KayPENTAX, Lincoln Park, NJ)19 to document voice use during five full work days for seven elementary music teachers (six females

€ dersten, et al Maria So

Voice Accumulator Information From a Database

and one male) and five female elementary classroom teachers. There were statistically significant differences between the groups for all measures with higher mean F0 (MF0), 269 Hz, for the female music teachers as compared with 236 Hz for the elementary teachers. The music teachers spoke with approximately 5 dB higher SPL, 82.3 dB, as compared with 77.2 dB for the classroom teachers. The phonation time was also significantly higher for the music teachers, as well as the cycle and distance dose parameters.7 Lyberg  Ahlander et al6 monitored 28 teachers (24 females and 4 males) with the APM during one working day and investigated the physical environment, such as room acoustics, activity noise level, and air quality. None of the teachers had a diagnosed voice disorder, but according to questions about voice symptoms, they were divided into two groups: voice symptoms (n ¼ 14) and vocally healthy (n ¼ 14). Interesting findings were that the female teachers with voice symptoms spoke with an MF0 of 234 Hz during teaching, which was significantly lower than the vocally healthy teachers’ value of 240 Hz. They also spoke with significantly lower SPL, 70 dB, than the vocally healthy, 74 dB. The correlation between F0 and SPL was negative in the group of teachers with voice symptoms. The authors proposed that this finding might reflect a voice disorder. A large study of 51 preschool teachers working in day care centers was conducted by Sala et al13 who used two noise exposure analyzers to measure speaking time, speech levels, and background noise levels during one working day. The results were compared with those for a control group of 25 nurses. The preschool teachers spoke significantly more (40% speaking time) than the nurses (28%), with significantly higher speech levels of an average 78 dB (at 30 cm), as compared with the nurses’ 72 dB; and in work environments with high background noise levels, too high for comfortable speech communication. The voice use of 12 vocally healthy preschool teachers was studied during 2 days, during and after work, by Szabo Portela et al.14 They found that the preschool teachers spoke with a high MF0 of 266 Hz during work, which decreased significantly to 246 Hz after work. Thus, also during leisure time, they spoke with a rather high pitch, in agreement with the teachers in the study by Hunter and Titze.5 The phonation ratio for the preschool teachers was 12% during work and significantly lower (5.5%) during leisure time. Thus, the phonation ratio was lower than what was found for teachers.5–7 To speak in high background noise levels at day cares, preschools, and schools have been identified as a potential risk factor for voice problems.4,6,13,20 Different vocal strategies have been found for 12 vocally healthy preschool teachers when they spoke in noisy preschool environments.12 Vocal behaviors in relation to background noise could merit further investigation, based on the findings by Lindstr€ om et al12 and Lyberg  Ahlander 6 et al, who found that teachers with voice symptoms did not increase F0 when they increased SPL, as would be expected in healthy voices.21 However, that behavior could also be interpreted as a strategy to reduce vocal loading. Very few studies have so far included patients with voice disorders. Watanabe et al18 compared variation in speaking time

646.e12

during 1 week in one female patient with spasmodic dysphonia. They used a speech accumulator and compared findings with a control group of 20 speakers. It was hypothesized that the patient would speak less than the control group because of her severe voice disorder; however, that was not the case. Thus, measuring the amount of voice use in daily life provides some documentation of a patient’s participation in different communicative situations. Other patients who may avoid participating in social situations because of their weak voice are individuals with Parkinson disease (PD). Schalling et al17 recently measured phonation time, voice SPL, and level of background noise with VoxLog (Sonvox AB, Ume a, Sweden) in five male patients and one female patient with PD during 4 days. Phonation time varied from 2.1% to 7.9% among the patients, suggesting that all except one patient spoke very little. On the other hand, it is not yet known how much vocally healthy elderly individuals speak in everyday life. The patients with PD spoke with a reduced vocal loudness level and raised the voice level significantly when they used the feedback system provided by the VoxLog device. When they spoke too softly, as determined individually, the VoxLog prompted them with tactile feedback.17 In summary, data from long-term monitoring can give quantitative evidence for high vocal loading and also information about participation in communicative situations. To understand the specific difficulties that patients with voice disorders may have in everyday situations, there is a need to collect data from patients with different voice disorders. Several attempts have been made to develop methods for documentation of long-term voice use in natural settings.22–28 A few portable recording systems have reached commercial status. Those are the APM, the VocaLog (Griffin Laboratories, Temecula, CA), and the VoxLog. Through the use of these systems, data can now be collected and compared by clinicians and researchers in different parts of the world and hopefully accelerate the gathering of information on mentioned parameters. The purpose of the present study was to use large long-term voice data, uploaded to a central database from different hospitals in Sweden, to investigate voice use and levels of background noise for patients with voice disorders and vocally healthy participants. This is the first study to present and analyze long-term voice use data from a common remote access database. Collecting such data is important to increase our knowledge regarding habitual voice behavior in patients with different voice disorders and identify potential risk factors related to work environment. The project was approved by the Regional Ethics Committee in Stockholm, Etikpr€ ovningsn€amnden, protocol 2011/2:1, project 2010/1953-31/2. METHOD VoxLog VoxLog is a small portable voice accumulator (90 3 60 3 15 mm) with both an accelerometer and a microphone placed in a neck collar (Figure 1A). The VoxLog is carried in a waist bag or fastened with a clip in a waistband (Figure 1B). The accelerometer detects pressure changes on

646.e13

Journal of Voice, Vol. 29, No. 5, 2015

FIGURE 1. A. The portable VoxLog is connected with a wire to the neck collar with the accelerometer and microphone in each end. B. The VoxLog is carried in a small bag or fastened with a clip into a waistband.

the neck generated by the vocal fold vibrations for measures of F0 (Hz) and phonation time (seconds). The microphone measures the SPL (dB SPL) of the voice and background noise. When the accelerometer detects phonation, the SPL is assumed to originate from the speaker’s voice. When there is no phonation, the device attributes the SPL at the microphone to the background noise (Figure 2). The microphone is calibrated for SPL and needs no further calibration during the recordings. The results are given in dB at the microphone and not corrected to any standard distance. The SPLs reported herein are therefore about 7 dB higher relative to a 30-cm microphone distance. The VoxLog needs to be

charged regularly (usually during the night) and can store data for up to 14 days. The recordings are transferred to VoxLog Connect, a software program that displays F0, voice and background noise levels, and phonation time (Figure 2). The data can also be uploaded to a remote central database or exported as text files for subsequent handling in spreadsheet and statistics software. Field testing VoxLog (firmware 1.11) and VoxLog Connect (version 2.1.1) were field tested for deployment in clinical practice by 29 speech-language pathologists (SLPs) working at nine hospitals in different parts of Sweden during 2010 and 2011. At the time of

FIGURE 2. Three channels as shown in the VoxLog Connect software program. The upper channel shows the fundamental frequency, the middle the voice SPL and background noise level, and the lowest phonation time. In the middle channel, it can be seen that the voice SPL is measured when phonation occurs as seen in the registrations of fundamental frequency (upper channel) and phonation time (bottom channel). When phonation does not occur, the level is interpreted as background noise.

€ dersten, et al Maria So

Voice Accumulator Information From a Database

data collection, the device’s time window for averaging data was set to 1 minute, meaning that means of F0 and SPL could be inspected down to 1 minute resolution in time. The SLPs were asked to use VoxLog in patients with voice disorders and on themselves or other vocally healthy persons in their circle of friends during 1–3 days. As part of the field-testing protocol, they were also asked to use the built-in database connection to upload any and all recordings to a central database. Hence, the material that was uploaded had not been stringently selected beforehand. The users, both the SLPs and the patients, also filled out a questionnaire about practical aspects of using VoxLog and possible problems. The answers have been reported elsewhere.29 Material Over the course of the field-testing period, a total of 153 files, from patients with voice disorders and vocally healthy persons, were uploaded to the remote database. Each file was inspected for validity. Some files were found to be very short (less than 1 hour), and some files did not contain reliable data. Data were considered unreliable when phonation appeared to be haphazardous, possibly because of poor contact between the accelerometer in the collar and the neck, or that the microphone cable had broken and did not register any sound level data at all. The recordings were made during 1, 2, or 3 days. Only data from participants with 2 days of reliable recordings were selected for analysis, so that comparison between 2 days could be made. Thus, data from 20 patients (16 females and 4 males) with different types of voice disorders and 10 vocally healthy individuals (eight females and two males) were included in the analysis. Background information for all participants is presented in Table 1. All participants had vocally demanding occupations, and all patients had been examined with laryngoscopy. Nine of the 16 female patients and three of the four male patients had functional voice disorders with vocal fatigue as the most prominent symptom. Some patients had organic lesions such as vocal fold nodules, Reinke edema, and vocal fold polyp (postsurgery), or neurological voice disorders (Table 1). Teacher was the most common occupation among the patients and the vocally healthy. The total number of recorded days was 60 (two for each participant), and the total recording time was 681 hours and 50 minutes. The recording time per day varied between participants, from 1 hour to 44 minutes (subject no. 27) to 14 hours and 55 minutes (subject no. 25). Data analysis Data were categorized according to gender and different diagnoses (Table 1). The files in the database were analyzed using Microsoft Excel (version 2010; Microsoft Corp, Redmond, WA). For each file, the following variables were calculated: recorded time, phonation time, average F0, F0 histogram with a bin width of 10 Hz, average voice SPL (of voiced speech only), and average SPL of the background noise (Table 2 and Table 3). Phonation time was calculated in seconds and presented in percent of the total recorded time. Thus, the term phonation ratio seems more appropriate and will be used henceforth. Voice data were also presented as speech range profiles.

646.e14

Statistics Descriptive statistics were calculated and presented for each participant and for each recording day, based on the large set of data obtained from the accelerometer and microphone, with one set of average values for every minute of recording. Coefficients of variation (CVs), expressed as the ratio of standard deviation and mean, were used to describe variations within each participant across each day. Pearson product moment correlation coefficients were used to test the relationship between MF0 and voice SPL as well as between voice SPL and background noise level. RESULTS Fundamental frequency MF0 and F0 mode for the 2 days are presented in Table 2. For the female patients with functional voice disorders (Id 1–9, Table 1), MF0 ranged from 190 (Id 1) to 278 Hz (Id 8). Two patients had Reinke edema (Id 10 and 11) and showed rather different values. Patient no. 10 had rather high MF0 values considering the diagnosis, 253 (day 1) and 250 Hz (day 2), suggesting a compensatory vocal behavior. Patient no. 11 had somewhat lower MF0 of 178 (day 1) and 181 Hz (day 2) probably reflecting the underlying edema. One of the male patients (Id 18), a salesperson with functional voice disorder, showed very high MF0 for a male speaker both days (170 and 168 Hz, respectively). It was notable that MF0 did not differ so much between day 1 and day 2 for either patients or vocally healthy participants. The CVs for MF0 showed a large variation ranging between 6.7% (Id 21) and 19% (Id 17). It can be noted that most participants showed rather similar CV values between day 1 and day 2 (Table 2). Phonation ratio The day-averaged phonation ratio varied considerably between individuals, from 1.2% (Id 5 during day 2) to 32.1% (Id 6 during day 1) as seen in Table 2. The highest value, 32.1%, was measured from a preschool teacher (Id 6) during day 1. She had a somewhat lower, but still high, phonation ratio of 22.9% during day 2. It was notable that most participants spoke about the same amount during day 1 and day 2. The phonation ratio differed less than 2% between the days for 12 of the 20 patients (Id 1, 3, 9–12, 14–18, and 20) and for six of the 10 vocally healthy participants (Id 23–25 and 28–30) as seen in Table 2. Voice SPL The average speaking voice SPL for 1 day ranged from 77.7 (Id 1) to 88.9 dB (Id 16) for the female patients and from 81.3 (Id 18) to 87.4 dB (Id 20) for the male patients (Table 3). The patients who spoke with the highest voice SPL were two preschool teachers (Id 6 and 16) and one teacher with vocal nodules (Id 12). The CV for voice SPL ranged from 3.4% for a female patient (Id 6) to 16.1% for a vocally healthy participant (Id 24). Background noise level The average background noise levels to which patients were exposed varied from 62.5 to 79.4 dB and were lower, 53.8–

646.e15

Journal of Voice, Vol. 29, No. 5, 2015

TABLE 1. Background Information for Identification of Participants (Id), Gender (Females ¼ F, Males ¼ M), Age in Years, Occupation, and Diagnosis for 20 Patients (P) With Voice Disorders (Id 1–20) and 10 Vocally Healthy (H) Persons (Id 21–30) and Length of the Recorded Time for Day 1 and Day 2 (Hours:Minutes) Recorded Time (Hours:Minutes) Id

Gender

Age

Occupation

Diagnoses

Day 1

Day 2

1P 2P 3P 4P 5P 6P 7P 8P 9P

F F F F F F F F F

48 48 45 36 39 34 37 21 49

Functional—vocal fatigue Functional—vocal fatigue Functional—vocal fatigue Functional—vocal fatigue Functional—vocal fatigue Functional—vocal fatigue Functional—vocal fatigue Functional—vocal fatigue Functional—vocal fatigue

08:56 13:58 05:04 10:38 14:21 05:59 13:47 13:39 06:55

11:43 13:58 10:09 13:58 05:45 07:29 08:20 13:36 08:17

10 P 11 P

F F

43 63

Reinke edema Reinke edema

12:47 09:37

13:58 08:42

12 P 13 P 14 P 15 P 16 P

F F F F F

41 29 40 42 43

Teacher Teacher Teacher Teacher Teacher Preschool teacher Worker at a press Telemarketing operator Informant in telephone environment Teacher Project leader (building environment) Teacher Cashier in department store Project leader (office) Preschool teacher Preschool teacher

13:16 04:33 12:12 14:36 06:17

13:58 13:26 14:01 10:20 05:21

17 P 18 P 19 P 20 P

M M M M

59 36 45 47

Chief Salesperson Office worker Own machine shop

13:58 10:01 12:37 14:58

13:57 10:22 13:55 12:29

21 H 22 H 23 H 24 H 25 H 26 H 27 H 28 H 29 H 30 H

F F F F F F F F M M

58 42 38 45 23 56 65 33 39 46

Teacher Teacher Teacher Teacher Telemarketing operator SLP SLP SLP Teacher Teacher

Vocal fold nodules Vocal fold nodules Habitual dysphonia Polyp (postsurgery) Vocal fold paresis (superior) and psychogenic disorder Functional—vocal fatigue Functional—vocal fatigue Functional—vocal fatigue Unilateral vocal fold paresis (recurrent nerve) Vocally healthy Vocally healthy Vocally healthy Vocally healthy Vocally healthy Vocally healthy Vocally healthy Vocally healthy Vocally healthy Vocally healthy

11:21 12:44 13:58 13:58 14:55 05:38 01:44 11:13 13:58 13:58

13:58 08:55 12:18 13:58 13:57 9:55 02:46 09:37 14:36 13:58

70.3 dB, for the vocally healthy participants. The highest average background noise level of 79.4 dB was measured for a teacher with functional voice disorder, with vocal fatigue as the most prominent symptom (Id 5). The CV for background noise level ranged considerably from 6.1% for one female patient (Id 9, day 1) to 23.1% (Id 4, day 1). Most CV values fell between 10% and 20% indicating that the average noise level varied considerably. Correlations between voice SPL and F0, and between voice SPL and background noise level Correlation coefficients for average voice SPL and MF0 measured during the whole recording each day varied considerably for the patients from r ¼ 0.08 to 0.79 and for the vocally healthy from 0.12 to 0.77. Correlation coefficients

for average voice SPL and background noise levels varied from r ¼ 0.10 to 0.71 and for the vocally healthy from r ¼ 0.17 to 0.65. The patient who showed the highest correlation between F0 and voice SPL (r ¼ 0.79) also showed the highest correlation between voice SPL and background noise level of r ¼ 0.71.

Speech range profiles To show variation in F0 and voice SPL simultaneously, data were presented as speech range profiles.30 Examples are given in Figure 3 from two patients, one teacher (Id 1), one preschool teacher (Id 6), and from one vocally healthy SLP (Id 26). It can be noted that the vocally healthy SLP varied her voice more than the two patients, both in F0 and SPL.

€ dersten, et al Maria So

646.e16

Voice Accumulator Information From a Database

TABLE 2. MF0, SD, CV, F0 Mode, and Phonation Ratio for Day 1 and Day 2 for 16 Female (F) and Four Male (M) Patients With Voice Disorders (P) and Eight Female and Two Male Vocally Healthy (H) Persons MF0 (SD) Hz Id 1P 2P 3P 4P 5P 6P 7P 8P 9P 10 P 11 P 12 P 13 P 14 P 15 P 16 P 17 P 18 P 19 P 20 P 21 H 22 H 23 H 24 H 25 H 26 H 27 H 28 H 29 H 30 H

CV (%)

F0 Mode (Hz)

Phonation Ratio (%)

Gender

Day 1

Day 2

Day 1

Day 2

Day 1

Day 2

Day 1

Day 2

F F F F F F F F F F F F F F F F M M M M F F F F F F F F M M

190 (17) 225 (28) 256 (28) 207 (26) 220 (27) 268 (19) 261 (35) 278 (30) 261 (30) 253 (37) 178 (21) 228 (29) 199 (16) 232 (30) 211 (26) 256 (40) 116 (22) 170 (18) 141 (15) 149 (17) 239 (16) 214 (40) 236 (31) 254 (38) 272 (26) 242 (31) 187 (21) 252 (46) 113 (18) 119 (16)

209 (20) 221 (30) 233 (28) 215 (17) 238 (30) 275 (21) 259 (30) 276 (26) 257 (29) 250 (35) 181 (20) 241 (24) 226 (22) 231 (31) 211 (25) 242 (28) 113 (18) 168 (17) 142 (15) 136 (16) 229 (17) 215 (35) 209 (24) 255 (34) 269 (24) 216 (31) 193 (26) 236 (30) 122 (19) 118 (15)

8.9 12.4 10.9 12.6 12.3 7.1 13.4 10.8 11.5 14.6 11.8 12.7 8.0 12.9 12.3 15.6 19.0 10.6 10.6 11.4 6.7 18.8 13.1 15.0 9.6 12.8 11.2 18.3 15.9 13.4

9.6 13.6 12.0 7.9 12.6 7.6 11.6 9.4 11.3 14.0 11.0 10.0 9.7 13.4 11.8 11.6 15.9 10.1 10.6 11.8 7.4 16.3 11.5 13.3 8.9 14.4 13.5 12.7 15.6 12.7

200 200 250 190 220 270 270 270 250 220 180 230 200 240 210 250 110 170 140 150 240 200 220 210 270 250 200 250 110 110

200 210 240 210 260 280 250 280 260 240 170 230 220 240 200 250 110 170 150 140 230 200 210 260 270 220 210 240 120 110

11.8 10.7 14.6 11.0 6.0 32.1 5.5 1.9 18.6 8.1 10.6 14.4 12.6 4.5 12.2 21.9 9.1 15.2 9.6 10.7 10.4 11.7 11.9 10.4 7.2 28.6 20.7 7.2 17.1 11.8

12.9 8.2 13.2 15.0 1.2 22.9 7.7 6.6 19.7 9.9 12.0 14.8 7.1 4.3 12.0 23.6 8.4 14.4 6.2 11.9 6.8 8.2 12.8 11.6 8.2 22.5 6.2 9.2 16.4 12.7

Abbreviation: SD, standard deviation; CV, coefficient of variation.

DISCUSSION This report presents voice data measured in natural communication situations from patients with voice disorders and vocally healthy participants through the use of a voice accumulator and a common remote access database. It is the first study to present such data collected in different hospitals in Sweden. MF0 was higher for most participants in the present study than previously reported Swedish reference values from text reading in a laboratory setting.31 For the present report, we did not have access to such laboratory recordings of the participants. The results are in agreement with previous studies,2–4 which showed that MF0 is higher when speaking in natural environments as compared with recordings of reading or habitual speech in a laboratory setting. This needs to be taken into account when results after voice interventions are based on voice recordings from laboratory settings. Thus, monitoring patients’ voice use in natural situations is a valuable tool to investigate if transfer of voice techniques learnt in therapy occurs or strategies to reduce vocal loading are used. We suggest that long-term voice

monitoring should be included as outcome measures after voice intervention in the future, especially for patients with occupational voice disorders. Voice SPL was measured at the microphone in the neck collar and was not adjusted for the distance between mouth and microphone, which varied somewhat between the participants. In the validation process of the VoxLog device, comparisons have been made between measured voice SPL at the microphone in the neck collar simultaneously with a microphone at 30 cm distance from the mouth. Roughly, 7 dB should be subtracted from voice SPL measured with VoxLog to correspond to 30 cm distance.29 The two female patients (Id 6 and Id 16) who had the highest phonation ratios for both day 1/day 2 (32.1/22.9% and 21.9/ 23.6%, respectively) were preschool teachers. They also spoke very loudly (88.2/88.1 and 88.9/86.8 dB), with a high average F0 (268/275 and 256/242 Hz) and high F0 mode (270/280 and 250/250 Hz). The levels of the background noise for those two patients were among the highest (68.7/71.6 and 70.3/

646.e17

Journal of Voice, Vol. 29, No. 5, 2015

TABLE 3. Average Voice SPL, Average Background Noise Level, SD, CV, Calculated for Day 1 and Day 2 for 16 Female (F) and Four Male (M) Patients With Voice Disorders (P) and Eight Female and Two Male Vocally Healthy (H) Persons Average Voice SPL (SD) dB Id 1P 2P 3P 4P 5P 6P 7P 8P 9P 10 P 11 P 12 P 13 P 14 P 15 P 16 P 17 P 18 P 19 P 20 P 21 H 22 H 23 H 24 H 25 H 26 H 27 H 28 H 29 H 30 H

Average Noise Level (SD) dB

CV (%)

CV (%)

Gender

Day 1

Day 2

Day 1

Day 2

Day 1

Day 2

Day 1

Day 2

F F F F F F F F F F F F F F F F M M M M F F F F F F F F M M

77.7 (4) 84.6 (6) 83.2 (7) 84.7 (11) 80.1 (6) 88.2 (3) 81.9 (6) 79.2 (6) 84.6 (4) 84.1 (7) 82.6 (6) 86.7 (5) 79.5 (5) 78.5 (8) 84.2 (5) 88.9 (6) 82.6 (6) 81.3 (7) 84.5 (7) 87.4 (6) 81.1 (6) 82.6 (10) 85.4 (7) 87.1 (14) 81.9 (4) 84.0 (6) 74.7 (5) 84.4 (7) 86.4 (6) 85.1 (6)

81.8 (4) 84.0 (8) 82.8 (7) 80.2 (7) 80.1 (5) 88.1 (4) 81.7 (6) 79.6 (5) 85.0 (6) 85.2 (7) 83.7 (7) 87.1 (4) 87.1 (5) 76.3 (8) 86.0 (6) 86.8 (5) 82.4 (6) 82.4 (8) 87.1 (7) 84.5 (6) 80.9 (6) 83.0 (6) 83.2 (8) 86.4 (7) 79.6 (4) 85.0 (9) 75.2 (8) 80.7 (6) 87.0 (7) 84.7 (6)

5.1 7.1 8.4 13.0 7.5 3.4 7.3 7.6 4.7 8.3 7.3 5.8 6.3 10.2 5.9 6.7 7.3 8.6 8.3 6.8 7.4 12.1 8.2 16.1 4.9 7.1 6.7 8.3 6.9 7.1

4.9 9.5 8.5 8.7 6.1 4.5 7.3 6.3 7.1 8.2 8.4 4.6 5.7 10.5 7.0 5.8 7.3 9.7 8.0 7.1 7.4 7.2 9.6 8.1 5.0 10.6 10.6 7.4 8.0 7.1

68.0 (9) 70.8 (9) 69.3 (9) 73.6 (17) 66.4 (15) 68.7 (5) 63.2 (6) 65.3 (8) 65.9 (4) 68.4 (9) 63.1 (6) 69.6 (8) 62.5 (7) 62.1 (9) 68.7 (6) 70.3 (5) 64.5 (8) 66.0 (12) 67.1 (9) 68.8 (9) 66.7 (8) 68.4 (12) 68.2 (8) 67.6 (11) 65.7 (12) 58.6 (10) 59.6 (8) 70.3 (9) 67.6 (8) 67.9 (8)

67.7 (9) 67.5 (8) 65.8 (11) 67.0 (8) 79.4 (12) 71.6 (6) 64.4 (6) 65.6 (7) 61.2 (14) 69.1 (12) 66.0 (9) 70.7 (7) 69.5 (8) 60.8 (8) 69.1 (6) 70.2 (5) 64.4 (6) 64.9 (9) 68.4 (9) 68.8 (7) 67.6 (8) 67.2 (11) 65.6 (9) 66.8 (10) 66.1 (8) 64.8 (11) 53.8 (7) 66.4 (8) 69.1 (7) 69.1 (10)

13.2 12.7 13.0 23.1 22.6 7.3 9.5 12.3 6.1 13.2 9.5 11.5 11.2 14.5 8.7 7.1 12.4 18.2 13.4 13.1 12.0 17.5 11.7 16.3 18.3 17.1 13.4 12.8 11.8 11.8

13.3 11.9 16.7 11.9 15.1 8.4 9.3 10.7 22.9 17.4 13.6 9.9 11.5 13.2 8.7 7.1 9.3 13.9 13.2 10.2 11.8 16.4 13.7 15.0 12.1 17.0 13.0 12.0 10.1 14.5

Abbreviation: SD, standard deviation; CV, coefficient of variation.

70.2 dB). These results support previous findings that preschool teachers have extremely vocally demanding work.4,13–15 The results also showed that those two patients, despite their voice disorders (Id 6 had a functional voice disorder and Id 16 vocal fold paresis and psychogenic voice disorder), probably used their voices as was required by their professions and not in a reduced or careful way. The data from the long-term voice monitoring can be used to guide patients to reduce vocal loading and not overuse their voices. Data from long-term monitoring can also increase employers’ understanding of work-related vocal loading. Our experience in the voice clinic is that data from long-term monitoring and quantification of voice use are pedagogical tools in communication with persons who are not voice specialists, such as employers, who actually are responsible for the work environment. In the present material, the number of participants with different voice disorders was small, and thus, it was not possible to analyze differences between groups based on voice diag-

nosis. However, because various types of voice disorders have not been studied to a large extent before, the data in the present study can be a start of collecting reference data from patients with different voice disorders. Most recordings in the present study were from morning to night including activities at home, at work, and leisure activities. In the data underlying this report, there were no descriptions of the activities and environments, which mean that the voice use could not be related to certain activities, which is a weakness of the study. The average background noise levels for the patients ranged from 62.5 to 79 dB, indicating that many of them probably had to increase the voice SPL to be heard. In 55 dB background noise level, one can speak with a comfortable voice and be heard at 1 m; at 70 dB, one must raise the voice and talk loudly to be heard at a distance of 1 m.32 Results from the correlations between voice SPL and background noise levels varied for the participants in accordance with results from Lindstr€om et al12 who found that preschool

€ dersten, et al Maria So

Voice Accumulator Information From a Database

646.e18

FIGURE 3. A–C. Examples of speech range profiles (SRPs) showing fundamental frequency (F0) on the x-axis and voice SPL on the y-axis. The area is the variation of F0 and voice SPL during day 1 (d1) and day 2 (d2). A. The SRP from one patient (Id 1) for both days. B. A preschool teacher with higher values for F0 and voice SPL (Id 6) than in (A). C. An SRP from a vocally healthy speaker (Id 26) with larger variations in frequency and voice SPL as compared with the SRPs in (A) and (B).

teachers at work used different strategies when adjusting their voice SPL to the background noise level. In future studies, the relationship between voice SPL and background noise level should be studied in greater detail and related to activities and room characteristics, such as acoustics and speaking distance.32,33 For analysis of voice behavior in different communicative situations, there is also a need to collect information about activities from diaries or written notes and information about subjective voice symptoms. To estimate the variation of voice use and background noise level during and between the 2 days, we used CVs. When summarizing those results, it was found that MF0 varied for most subjects more than 10% during each recording day, whereas the CVs for average voice level were below 10% for most subjects. The level of background noise varied considerably for most subjects, between 10% and 20%. Given that data collection is time consuming and often involves practical and administrative problems,34 it would be valuable if the amount of data needed to give a representative picture of the voice use could be stated. Hunter and Titze5 recorded 57 teachers during 14 days using the National Center for Voice and Speech voice dosimeter, whereas Morrow and Connor7 who used the APM system (model 3200; KayPENTAX) claimed that a full working week for teachers would

show a reliable picture of the voice use. Thorsdotter et al35 compared data collected with VoxLog during 2 weeks from three female patients and three workplace-matched vocally healthy controls. They found differences between the first and second weeks mainly because of a sick leave and an allergic reaction to the neck collar but not with regard to average voice use. Mehta et al36 tried to estimate the duration needed to accurately measure voice use in patients with voice disorders and a control group using percent error variation. In total, 10 subjects’ voices were monitored during at least 40 hours. Average F0 decreased to 1% after 12 hours and voice SPL to 1% after 20 hours. For the phonation time, cycle dose, and distance dose variables, the percent error variation was larger. No differences were found between the patient and vocally healthy groups. Intersubject variation was large in both the study by Mehta et al36 and the present study. Thus, we need information from larger groups of patients and vocally healthy speakers to document potential differences or similarities between those groups. VoxLog and the use of a remote central database seem to be useful for large data collection and analysis regarding averaging of the voice parameters and background noise level. When analysis is to be performed from a large number of files in a database, and also analyze variations, there is a need for research-specific tools to simplify that procedure.

646.e19 CONCLUSIONS The use of a remote access central database and strict protocols can accelerate data collection from larger groups of participants and contribute to establishing reference values regarding voice use in natural situations and from patients with voice disorders. Information about activities and voice symptoms would supplement the objective data and is recommended in future studies.

Acknowledgments Thanks to all SLPs from different hospitals in Sweden for recruiting participants, doing the recordings, and uploading the VoxLog files to the central database, and to Elisabeth Berg, at the Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, for statistical advice. The project was supported by the Swedish Governmental Agency for Innovation Systems (VINNOVA, grant number 2010–00597) and by a grant from The Aina B€ orjeson Foundation for speech language pathology research and treatment.

REFERENCES 1. Hillman RE, Heaton JT, Masaki A, Zeitels SM, Cheyne HA. Ambulatory monitoring of disordered voices. Ann Otol Rhinol Laryngol. 2006;115: 795–801. 2. McAllister A, Brandt SK. A comparison of recordings of sentences and spontaneous speech: perceptual and acoustic measures in pre-school childrens’ voices. J Voice. 2012;26:673–677. 3. Rantala L, Lindholm P, Vilkman E. F0 change due to voice loading under laboratory and field conditions. A pilot study. Logoped Phoniatr Vocol. 1998;23:164–168. 4. S€odersten M, Granqvist S, Hammarberg B, Szabo A. Vocal behavior and vocal loading factors for preschool teachers at work studied with binaural DAT recordings. J Voice. 2002;16:356–371. 5. Hunter EJ, Titze IR. Variations in intensity, fundamental frequency, and voicing for teachers in occupational versus nonoccupational settings. J Speech Lang Hear Res. 2010;53:862–875. 6. Lyberg  Ahlander V, Pelegrı´n Garcı´a D, Rydell R, L€ofqvist A. Teachers’ voice use in teaching environments: a field study using ambulatory phonation monitor. J Voice. 2014;28:841.e5-841.e15. 7. Morrow SL, Connor N. Comparison of voice-use profiles between elementary classroom and music teachers. J Voice. 2011;25:367–372. 8. Rantala L, Vilkman E. Relationship between subjective voice complaints and acoustic parameters in female teachers’ voices. J Voice. 1999;13:484–495. 9. Rantala L, Vilkman E, Bloigu R. Voice changes during work: subjective complaints and objective measurements for female primary and secondary schoolteachers. J Voice. 2002;16:344–355. 10. Titze IR, Hunter EJ, Svec JG. Voicing and silence periods in daily and weekly vocalizations of teachers. J Acoust Soc Am. 2007;121:469–478. 11. Lindstr€ om F, Ohlsson AC, Sj€oholm J, Waye KP. Mean F0 values obtained through standard phrase pronunciation compared with values obtained from the normal work environment: a study on teacher and child voices performed in a preschool environment. J Voice. 2010;24: 319–323. 12. Lindstr€ om F, Waye KP, S€odersten M, McAllister A, Ternstr€om S. Observations of the relationship between noise exposure and preschool teacher voice usage in day-care center environments. J Voice. 2011;25:166–172. 13. Sala E, Airo E, Olkinuora P, Simberg S, et al. Vocal loading among day care center teachers. Logoped Phoniatr Vocol. 2002;27:21–28.

Journal of Voice, Vol. 29, No. 5, 2015 14. Szabo Portela A, Hammarberg B, S€odersten M. F0 and phonation time in vocally healthy pre-school teachers measured with a voice accumulator. Folia Phoniatr Logop. 2013;65:84–90. 15. Szabo A, Hammarberg B, Granqvist S, S€odersten M. Methods to study preschool teachers’ voice at work: simultaneous recordings with a voice accumulator and a DAT recorder. Logoped Phoniatr Vocol. 2003;28:29–39. 16. Schloneger MJ. Graduate student voice use and vocal efficiency in an opera rehearsal week: a case study. J Voice. 2011;25:265–273. 17. Schalling E, Gustafsson J, Ternstr€om S, S€odersten M. Effects of tactile biofeedback by a portable voice accumulator on voice sound level in speakers with Parkinson disease. J Voice. 2013;27:729–737. 18. Watanabe H, Shin T, Oda M, Fukaura J, Komiyama S. Measurement of total actual speaking time in a patient with spastic dysphonia. Folia Phoniatr Logop. 1987;39:65–70. 19. Cheyne HA, Hanson HM, Genereux RP, Stevens KN, Hillman RE. Development and testing of a portable vocal accumulator. J Speech Lang Hear Res. 2003;46:1457–1467. 20. McAllister A, Granqvist S, Sj€olander P, Sundberg J. Child voice and noise: a pilot study of the effect of a day at the day-care on ten children’s voice quality according to perceptual evaluation. J Voice. 2009;23:587–593. 21. Gramming P. Vocal loudness and frequency capabilities of the voice. J Voice. 1991;5:144–157. 22. Airo E, Olkinuora P, Sala E. A method to measure speaking time and speech sound pressure level. Folia Phoniatr Logop. 2000;52:275–288. 23. Buekers R, Bierens E, Kingma H, Marres EH. Vocal load as measured by the voice accumulator. Folia Phoniatr Logop. 1995;47:252–261. 24. Granqvist S. The self-to-other ratio applied as a phonation detector for voice accumulation. Logoped Phoniatr Vocol. 2003;28:71–80. 25. Masuda T, Ikeda Y, Manako H, Komiyama S. Analysis of vocal abuse: fluctuations in phonation time and intensity in 4 groups of speakers. Acta Otolaryngol. 1993;113:547–552. 26. Ohlsson A-C, Brink O, L€ofqvist A. A voice accumulator—validation and application. J Speech Hear Res. 1989;32:451–457. 27. Ryu S, Komiyama S, Kannae S, Watanabe H. A newly devised speech accumulator. ORL J Otorhinolaryngol Relat Spec. 1983;45:108–114. 28. Titze IR, Svec JG, Popolo PS. Vocal dose measures: quantifying accumulated vibration exposure in vocal fold tissues. J Speech Lang Hear Res. 2003;46:919–932. 29. Wirebrand M. VoxLog Report. Stockholm, Sweden, Sweden’s Innovation Agency; 2012. 30. Hallin A-E, Fr€ost K, Holmberg EB, S€odersten M. Voice and speech range profiles and Voice Handicap Index for males—methodological issues and data. Logoped Phoniatr Vocol. 2012;37:47–61. 31. Pegoraro Krook I. Speaking fundamental frequency characteristics of normal Swedish subjects obtained by glottal frequency analysis. Folia Phoniatr (Basel). 1988;40:82–90. 32. Pekkarinen E, Viljanen V. Acoustic conditions for speech communication in classrooms. Scand Audiol. 1991;20:257–263. 33. Lyberg- Ahlander V, Rydell R, L€ofqvist A. Speaker’s comfort in teaching environments: voice problems in Swedish teaching staff. J Voice. 2012; 26:149–161. 34. Nix J, Svec J, Laukkanen A-M, Titze I. Protocol challenges for on-the-job voice dosimetry of teachers in the United States and Finland. J Voice. 2007; 4:385–396. 35. Thorsdotter M, Ternstr€om S, S€odersten M. Voice use measured during work and leisure using the new portable voice accumulator Voxlog: a methodological study. Paper presented at: The 9th Pan European Voice Conference; August 31-September 3, 2011; Marseille, France. 36. Mehta DD, Woodbury Listfield R, Cheyne HA, Heaton JT, Feng SW, Za~nartu M, Hillman RE. Duration of ambulatory monitoring needed to accurately estimate voice use. Presented at: Proceedings of InterSpeech: Annual Conference of the International Speech Communication Association; September 9-13, 2012; Portland, OR.