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Voice Characteristics of Female Physical Education Student Teachers
Voice Characteristics of Female Physical Education Student Teachers Elizabeth U. Grillo and Justine Fugowski, West Chester, Pennsylvania Summary: In this study, the subjective and objective voice measures of seven female physical education student teachers during a semester of student teaching were investigated. The participants completed the voice measures at three data collection time points: baseline, middle, and end of the semester. The voice measures included acoustic and aerodynamic data, perceptual rating scales of vocal quality and vocal fatigue, an end-of-semester questionnaire, and the Voice Handicap Index. Results demonstrated that the subjective and objective voice measures changed at the middle and the end of the semester as compared with those at baseline. The change in the voice measures may suggest that the vocal mechanism was adapting to the increased vocal demands of teaching physical education. Key Words: Voice–Student teachers–Acoustic–Aerodynamic–Self-rating scales–Voice Handicap Index.
INTRODUCTION Research has provided insight into the prevalence of voice disorders in teachers.1–8 Results of the research indicate that between 15% and 32% of teachers reported experiencing a voice disorder in their teaching career.1–3 Teachers were also more likely to report vocal problems and physical discomfort associated with a vocal disorder as compared with the nonteacher population.2 Additionally, student teachers, who primarily comprise young individuals at the beginning of their careers, reported a high prevalence of voice complaints.4 Female teachers were also more likely to report voice problems during their teaching careers than male teachers.5 In fact, the prevalence of voice disorders in male teachers is 13% as compared with 22% in female teachers; therefore, perhaps the female gender can be considered as a risk factor for the development of voice disorders in teachers.5 The literature also contains studies that have investigated the relationship of the subject taught and the role of age and the length of years of teaching on the voices of teachers.2,5–8 Results suggest that physical education teachers are at a higher risk for reporting voice disorders.6 In fact, 41% of the physical education teachers who participated in the study reported a voice problem.6 Researchers and clinicians have hypothesized that yelling over long distances or for long durations without amplification might contribute to the voice difficulties reported by physical education teachers.6 Research investigating the influence of age and length of teaching career on the voices of teachers has been inconclusive with mixed findings.2,5–8 Smith et al6 investigated the age and years of teaching and found no association between the two factors. Conversely, another study by Smith et al2 found that the number of vocal problems reported by teachers increased with age and the number of years of employment. Other studies conducted by Kooijman et al7 and Simberg et al8 found no relationship between the number Accepted for publication December 7, 2009. From the Department of Communicative Disorders, College of Health Sciences, West Chester University, West Chester, Pennsylvania. Address correspondence and reprint requests to Elizabeth U. Grillo, Department of Communicative Disorders, West Chester University, 201 Carter Drive, West Chester, PA 19383. E-mail: [email protected] Journal of Voice, Vol. 25, No. 3, pp. e149-e157 0892-1997/$36.00 Ó 2011 The Voice Foundation doi:10.1016/j.jvoice.2009.12.001
of teaching years and the prevalence of voice disorders in teachers. In another study, a higher prevalence of voice disorders was found in teachers between the ages of 31 and 40 years, but no significant relationship was found between the duration that the teachers had been employed and the prevalence of a voice disorder.5 Based on the contradictory findings presented previously, it is not clear if age and length of employment play a role in the prevalence of voice disorders in teachers. Researchers have not focused on the prevalence of voice disorders in student teachers, perhaps, because there is no clear evidence that voice disorders have an onset because of age or duration of years of teaching. Consequently, minimal research has been conducted concerning voice disorders among student teachers.4,9 Most of the literature has predominantly focused on the prevalence of voice disorders in teachers through survey research.1–8 However, there are some experimental studies that have provided laryngostroboscopic, acoustic, and perceptual data in both teachers and student teachers.9–14 Stroboscopic data revealed irregular vocal fold vibrations, incomplete glottal closure, and soft vocal nodules as a baseline vocal fold pattern in teachers.10 Acoustic measures collected after vocal loading demonstrated an increase in fundamental frequency (F0), jitter, relative average perturbation, shimmer, and amplitude perturbation among teachers and nonteachers.10–14 After vocal loading, teachers and nonteachers demonstrated deterioration in mucosal wave propagation and incomplete glottal closure.11,14 One study demonstrated that student teachers who participated in voice therapy and vocal hygiene education had improved jitter, shimmer, F0, and glottal closure,9 therefore, supporting a voice disorders prevention paradigm at the training level of student teachers. Although this body of research has provided insight into the prevalence of voice disorders in teachers and some objective voice data among teachers, further work is required to assess the impact of teaching on the voices of student teachers. Only one study has investigated acoustic, laryngostroboscopic, and perceptual voice measures in student teachers, but no study to date has focused on female physical education student teachers.9 It is important to consider female student teachers, because female teachers are at a higher risk for developing a voice disorder.5 In addition, much of the research has not
e150 assessed the effect of the subject taught on the voices of teachers and student teachers. Physical education teachers had a higher probability of reporting voice difficulties; therefore, teaching physical education might be considered a risk factor for developing a voice disorder.6 Most of the research focused on a series of continuous days or several time points within the day but failed to provide objective information on voice characteristics over the course of weeks or months. Conducting research in a longitudinal manner will provide a more accurate representation of what happens to the voices of student teachers during their student-teaching experience. Based on the high prevalence of voice disorders in the teaching profession, a prevention paradigm should be developed to minimize the likelihood of developing a voice disorder. The literature emphasizes the need for vocal education in the teaching profession.7,15 Because the teaching profession is at such a high risk for developing voice problems, teachers should be educated on how to compensate for the voice demands of their occupation.2 This voice disorder prevention paradigm for teachers must begin at the training level in the education of student teachers. With the goal of developing such a prevention paradigm beginning at the training level, it must be understood and evaluated what happens to the voices of student teachers during a semester of student teaching. Considering the gaps in the literature, the purpose of this study was to investigate the subjective and objective voice characteristics of female physical education student teachers during a semester of student teaching. The specific research questions were (1) will the subjective and objective voice measures of female physical education student teachers change during the semester of student teaching; (2) will the changes be consistent across the subjective and objective voice measures; and (3) will vocal quality and/or vocal fatigue impact the student teachers’ teaching abilities during the semester? METHODS Participants The participants, comprised of seven female physical education student teachers, enrolled in the undergraduate teacher education program at West Chester University in West Chester, Pennsylvania. One participant was a singer. Females were chosen because of the high prevalence of voice disorders among female teachers.5 Physical education teachers were more likely than teachers who taught other disciplines to report voice disorders6; therefore, physical education student teachers participated in the study. The physical education student teachers completed their 14-week student teaching semester at both the primary education level (ie, elementary school) and the secondary education level (ie, high school), spending 7 weeks at each level. A typical school day consisted of 7–8 hours of talking in physical education or health classes in large gymnasiums or classrooms. After informed consent, participants completed screening procedures. The screening consisted of a questionnaire and a puretone hearing screening at 20 dB for the following frequencies: 500, 1000, 2000, and 4000 Hz. The inclusion criteria were as follows: female gender, ages 20–25 years, physical education student teacher, first semester of student teaching, normal
Journal of Voice, Vol. 25, No. 3, 2011
hearing as determined by passing the pure-tone hearing screening, and no current voice problem. If the participants met the inclusion criteria, they were enrolled in the study. After enrollment in the study, participants were required to complete the collection of voice data at three time points in the semester. The first time point for data collection occurred before the participants began their first semester of student teaching immediately after screening procedures on a week day during the semester break between fall and spring semesters (ie, baseline). Participants returned midway through the semester after a full day of teaching to collect data for the second time point approximately 7 weeks after baseline (ie, middle of the semester). The third time point occurred at the conclusion of the participants’ student teaching practicum semester after a full day of teaching approximately 7 weeks after the middle of the semester (ie, end of the semester). All measures collected during the first time point served as each participant’s baseline for later comparison with the second and third time points. The participants also completed an informal interview at baseline, middle of the semester, and end of the semester inquiring about their student teaching experience and their voice production. Instruments Several subjective and objective measures were administered at three data collection time points throughout the semester of student teaching. For the subjective measures, self-rating scales of vocal quality and vocal fatigue were given to the participants along with the end-of-semester questionnaire and the Voice Handicap Index (VHI)16 (Appendices A–C). The subjective measures were completed by the participants. The objective measures included acoustic and aerodynamic data. Acoustic measurements were collected by the experimenter using the Multidimensional Voice Program software program by KayPentax (Lincoln Park, NJ) on a Dell desktop computer using a head-mounted microphone (AKG with a frequency response of 20–20 000 Hz and sensitivity at 1000 Hz of 7 mV/Pa) 3 inches from the mouth. Various acoustic measurements were elicited from sustained phonation of /a/ for 3 seconds in a typical speaking voice for each data collection time point. From sustained phonation, the acoustic measures of F0, absolute jitter, and percent shimmer were collected. Sustained phonation of /a/ was used, because it involves a relatively open vocal tract with limited oral-pharyngeal constriction, whereas connected speech involves dynamic changes between open vocal tract for vowels and very constricted oral-pharyngeal patterns for different types of consonants.17 As a result, a more accurate representation of vocal fold vibration can be observed with measures collected during sustained phonation because of the lack of articulator interference. Absolute jitter and percent shimmer were selected for the study, because they are based on differences between successive periods or amplitudes of the speaker’s F0 and sound pressure level, respectively. In addition, to be consistent with previous studies that assessed changes in jitter and shimmer measures of student teachers who underwent voice therapy9 and of teachers pre- and post-vocal loading10–14 absolute jitter and percent shimmer were selected for the present study. Aerodynamic data were captured using the Global Voice Analyzer, which includes a circumferentially vented face mask
Elizabeth U. Grillo and Justine Fugowski
Voice Characteristics of Student Teachers
with attached airflow (model number 1Inch-D-4V) and pressure (model number 10Inch-D-4V) transducers, manufactured by All Sensors (Morgan Hill, CA). The airflow-measurement equipment was calibrated for aerodynamic functions before each day’s data collection using a Dwyer (Michigan City, IN) U tube manometer for pressure and a Glottal Enterprises (Syracuse, NY) pneumotach calibration unit for airflow. Participants placed a vented mask over their mouth and nose, while positioning plastic tubing intraorally connected to the pressure transducer, avoiding blockage of the tube by the tongue. A strap was placed around the participant’s head and tightened to secure a tight seal with the participant’s face. After the experimenter checked the mask positioning to verify the seal, the participant was trained to produce a five-syllable consonant-vowel syllable string (/pi pi pi pi pi/) repeated three times at an approximate rate of 88 beats per minute in a typical speaking voice.18 A metronome was used to provide the beat pattern (88 beats per minute) for production of consonant/vowel strings (/pi/). Subglottic pressures (Ps) were estimated from oral pressures for each trial using software that obtained the interpolated pressure between pressure peaks two and three, three and four, and four and five for each /pi pi pi pi pi/ string as well as the time-locked average airflow for those syllables.18 Laryngeal resistance (ie, LR: Ps divided by average airflow, cm H2O/L/s19) was calculated from the combination of the estimated Ps and subsequent average airflow. Summary files were generated by the software program that indicated Ps, airflow, and LR. Maximum phonation time (MPT) during sustained /a/ and the s/z ratio were also captured and averaged across three trials for each data collection time point. MPT and the s/z ratio were collected because they provide information related to the balance of airflow with phonation, do not require instrumentation, and therefore, are typical clinical measures. With the exception of the consent form, screening procedures, and the end-of-semester questionnaire, the same methods and order of procedures were used in each of the three data collection sessions (Appendix D). Because of the small participant number, descriptive analyses were chosen to represent the results most effectively. Cohen’s d and the effect size correlation r were used to measure the strength of the relationship between two variables. Cohen’s d was calculated as the difference between the means divided by a standard deviation. The equation used for Cohen’s d was d ¼ x1 x2 s with s defined as sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðn1 1Þs21 þ ðn2 1Þs22 : s¼ n1 þn Cohen’s d was calculated three times for each of the numerical dependent variables comparing baseline with middle of the semester, middle of the semester with end of the semester, and baseline with end of the semester. The effect size correlation r was also computed from Cohen’s d for each of the numerical dependent variables across the time point comparisons.
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RESULTS Acoustic measures The means and standard deviations of F0, absolute jitter, and percent shimmer during sustained phonation of /a/ were collected at three time points: baseline, middle, and end of the semester of student teaching (Table 1). Compared with baseline for each of the seven participants, the means and standard deviations of F0, absolute jitter, and percent shimmer increased at the middle and the end of the semester. Cohen’s d and the effect size correlation r, at the three time point comparisons for F0, absolute jitter, and percent shimmer, demonstrated effect sizes ranging from small (ie, 0.1–0.3) to medium (ie, 0.5) (Table 2). Aerodynamic measures The means and standard deviations of LR, Ps, and average airflow were calculated at each of the time points from three repetitions of /pi pi pi pi pi/ for a total of 15 /pi/s (Table 3). Mean LR decreased from baseline at the middle of the semester and then increased from baseline at the end of the semester. Collectively, the mean Ps increased at the middle and the end of the semester as compared with that at baseline. The mean airflow rate increased from baseline at the middle of the semester and then decreased at the end of the semester but did not return to baseline. The means and standard deviations of MPT and the s/z ratio were calculated at each time point (Table 3). Overall, the MPT decreased from baseline at the middle of the semester and then increased at the end of the semester but did not exceed the baseline value. Overall, the mean s/z ratio increased from baseline at the middle of the semester and at the end of the semester. Cohen’s d and the effect size correlation r, at the three time point comparisons for LR, Ps, average airflow, MPT, and the s/z ratio, demonstrated effect sizes ranging from small to large (ie, 0.8) (Table 4). Participant rating scales The participants were asked to evaluate their vocal quality and vocal fatigue by completing the self-rating scales at each of the three data collection time points (Appendices A and B). All ratings involving pitch and loudness remained consistent throughout the semester. For example, at baseline, middle, and end of the semester, six participants reported that pitch was ‘‘just right,’’ and one participant reported that pitch was ‘‘too low.’’ For loudness, at baseline, middle, and end of the semester, six of the participants reported that loudness was ‘‘just right,’’ and one participant reported that loudness was ‘‘too loud.’’ Additionally, the participants rated overall vocal quality and vocal fatigue. At the baseline time point, all seven participants rated their voice as sounding ‘‘clear’’ and three of the seven participants reported experiencing vocal fatigue ‘‘sometimes.’’ By the middle of the semester, six participants reported negative voice quality changes. Specifically, three participants reported a ‘‘hoarse’’ voice, and three participants reported a ‘‘strained or raspy’’ voice at the middle of the semester. At the middle of the semester interview, two of the seven participants reported ‘‘voice loss’’ for the first few weeks of the semester. Related to vocal fatigue, six participants reported experiencing vocal
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TABLE 1. Means and Standard Deviations of F0, Absolute Jitter, and Percent Shimmer During Sustained Phonation of /a/ at the Three Time Points
TABLE 2. Cohen’s d and Effect Size Correlation r of F0, Absolute Jitter, and Percent Shimmer During Sustained Phonation of /a/ at the Three Time Point Comparisons
Acoustic Measure
Acoustic Measure
Time Point
Mean
Standard Deviation
F0 (Hz)
1 2 3
195.38 198.98 208.91
8.11 11.09 15.24
Absolute jitter
1 2 3
41.09 43.07 51.34
9.45 11.96 16.76
Percent shimmer
1 2 3
2.63 3.02 3.19
0.17 0.32 0.60
1, Baseline; 2, middle of the semester; 3, end of the semester.
fatigue by the middle of the semester ‘‘sometimes,’’ which is a 50% increase from baseline. Although six participants reported negative voice quality changes and an increase in vocal fatigue at the middle of the semester, all six participants reported that they were successful in adapting to the vocal demands of teaching. By the end of the semester, voice quality ratings improved, whereas vocal fatigue ratings remained the same from the middle of the semester. For voice quality, six participants rated their voice as ‘‘clear,’’ and one participant rated her voice as ‘‘hoarse’’ by the end of the semester. At both the middle and the end-of-semester time points, all seven participants reported that their vocal quality and vocal fatigue were not affecting their teaching ability. At the conclusion of subjective and objective data collection at the end of the semester, the participants were administered the end-of-semester questionnaire to gain additional information about their vocal quality and student teaching experiences (Appendix C). The participants were asked to compare their vocal quality at the end of the semester with that at baseline. All of the seven participants reported that their vocal quality was not worse at the end of the semester as compared with that at baseline, but six participants reported that their vocal quality was different at the end of the semester as compared with that at baseline. Out of the six participants who responded that their vocal quality was different, four participants reported that their voice had become stronger, gained stamina, and/or adapted to vocal demands. Additionally, two participants reported a strained, scratchy, lower-pitched voice at the end of the semester as compared with that at baseline. The participants also compared their vocal fatigue at the end of the semester with that at baseline. Five participants reported that they did not feel increased vocal fatigue at the end of the semester as compared with that at baseline. Two participants reported that they did experience increased vocal fatigue at the end of the semester as compared with that at baseline. Participants also completed the VHI at all three time points. Overall, compared the baseline value for each of the seven participants, the VHI value decreased both at the middle and the end of the semester
Time Point Comparisons
Cohen’s d
Effect Size r
F0 (Hz)
B–M M–E B–E
1.12 0.37 0.75
0.48 0.18 0.35
Absolute jitter
B–M M–E B–E
0.18 0.56 0.75
0.09 0.27 0.35
Percent shimmer
B–M M–E B–E
1.54 0.35 1.35
0.61 0.17 0.54
Abbreviations: B–M, baseline to middle of the semester; M–E, middle of the semester to end of the semester; B–E, baseline to end of the semester
(Table 5). In addition, Cohen’s d and the effect size correlation r for the VHI indicated a negative change from baseline at the middle and the end of the semester, ranging from a medium to a large effect size. DISCUSSION The first two experimental questions investigated the extent to which the subjective and objective measures of the participants’ voices changed during a semester of student teaching and whether or not the changes were consistent across the subjective and objective voice measures. Based on the analysis of the results, it is clear that the subjective and objective voice parameters of the student teachers changed across the semester. Related to acoustics, the means and standard deviations of F0, absolute jitter, and percent shimmer increased at the middle and the end of the semester as compared with those at baseline, possibly indicating an increase in variability of vocal fold vibration as the voice demands of the student teachers increased throughout the semester of student teaching. Changes noted in the acoustic measures at the middle of the semester also coincided with the subjective difficulties noted by the participants. In the present study, considering the intense voice demands for student teaching across the semester, the increases observed in F0, absolute jitter, and percent shimmer were consistent with the results of previous research immediately after vocal loading.10–14 For the acoustic measures, the effect sizes ranged from 0.09 to 0.61, indicating a small to medium clinical difference among the baseline, middle, and end of the semester time points. This finding was possibly because of the variability in the acoustic measures. For example, Carding et al20 reported poor to moderate retest reliability and poor sensitivity to change for jitter and shimmer measures. In addition, reported normative values of jitter and shimmer vary considerably among studies,21–23 thus suggesting the highly variable nature of jitter and shimmer measures. Changes were also noted throughout the semester for the aerodynamic measures of LR, Ps, airflow, MPT, and the s/z ratio.
Elizabeth U. Grillo and Justine Fugowski
TABLE 3. Means and Standard Deviations of LR, Ps, Airflow, MPT, and the s/z Ratio at the Three Time Points Aerodynamic Measure LR (cm H2O/L/s)
Ps (cm H2O)
Airflow (mL/s)
MPT (s)
s/z Ratio
Time Point
Mean
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Standard Deviation
TABLE 4. Cohen’s d and Effect Size Correlation r of LR, Ps, Airflow, MPT, and the s/z Ratio at the Three Time Point Comparisons Aerodynamic Measure
Time Point Comparisons
Cohen’s d
Effect Size r
LR (cm H2O/L/s)
B–M M–E B–E
1.22 1.13 0.21
0.53 0.49 0.10
Ps (cm H2O)
B–M M–E B–E
0.92 1.65 2.54
0.42 0.63 0.78
Airflow (mL/s)
B–M M–E B–E
2.43 1.32 0.97
0.77 0.54 0.43
1 2 3
16.51 14.29 17.05
2.03 1.50 3.09
1 2 3
3.01 3.18 3.48
0.19 0.18 0.19
1 2 3
209.04 277.00 237.57
26.66 29.46 32.16
1 2 3
20.33 18.80 19.23
2.64 2.02 2.34
MPT (s)
1 2 3
1.15 1.22 1.90
0.19 0.19 0.13
B–M M–E B–E
0.65 0.19 0.50
0.31 0.09 0.24
s/z Ratio
B–M M–E B–E
0.37 4.25 4.67
0.18 0.90 0.92
1, Baseline; 2, middle of the semester; 3, end of the semester.
B–M, baseline to middle of the semester; M–E, middle of the semester to end of the semester; B–E, baseline to end of the semester.
The fluctuation of the mean LR values can possibly be a result of adaptation to increased vocal demands throughout the semester of student teaching. Specifically, the decrease in LR at the middle of the semester was consistent with the changes in other objective measures and also with subjective comments of the participants that a period of voice change occurred at the middle of the semester. The voice change, at the middle of the semester, was characterized by six of the participants as ‘‘hoarse or strained/raspy,’’ suggestive of decreased resistance to the flow of air, possibly because of incomplete glottal closure.11,14,24,25 The consecutive increase of the mean Ps at the middle and the end of the semester can possibly be attributed to compensation techniques developed by the student teachers to produce a louder vocal quality as the semester of student teaching progressed.18 The fluctuation of mean airflow rates across the semester can possibly be because of the participants’ vocal folds adapting to increased vocal demands throughout the semester of student teaching. Specifically, the increase in mean airflow rate at the middle of the semester might indicate an incomplete glottal closure pattern as seen in previous research after vocal loading in teachers and nonteachers.11,14 The trend in MPT and the s/z ratio was also consistent with LR, mean airflow rates, and subjective comments of the participants. Specifically, at the middle of the semester, MPT and the /z/ portion of the s/z ratio were not as long as those at baseline, possibly indicating difficulties in coordinating respiration with vocal fold vibration because of incomplete glottal closure.11,14 For the aerodynamic measures, the effect sizes ranged from 0.09 to 0.92, with some effects demonstrating a change in the negative direction, indicating a decrease in the numerical value of the dependent variable. The magnitude of the clinical difference ranged from small to large depending on the aerodynamic measure.
Much like the objective measures, several subjective measures changed from baseline at the middle and the end of the semester; for example, an increase in the number of participants who experienced vocal fatigue and who reported negative changes in vocal quality was noted at the middle of the semester. By the end of the semester, however, some of the subjective and objective measures demonstrated closer approximations to baseline levels; for example, better coordination of respiration during phonation (eg, MPT) and a decrease in the number of participants who reported negative voice quality changes. The voice changes, at the middle of the semester, could be attributed to the vocal mechanism negatively reacting to the new skill of increased vocal demands necessary for teaching physical education. Conversely, at the end of the semester, the improvements in voice, closer to baseline levels, might be suggestive of the vocal mechanism adapting positively to the vocal demands of teaching physical education as the newly learned skill was stabilized. A similar trend has been documented in the motor learning literature, where a negative practice effect can occur characterized by a period of increased errors when learning a new skill.26–29 After this period of increased errors, the errors decrease as the newly learned skill is stabilized.26–29 The end goal of the participants was to learn a new voice pattern for the increased vocal demands of teaching physical education. At the middle of the semester, the participants were possibly experiencing a negative practice effect as evidenced by the change in subjective and objective voice measures from baseline. By the end of the semester, the new voice pattern was stabilized, as evidenced by most of the subjective and objective voice measures returning closer to those at baseline levels.
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TABLE 5. Means and Standard Deviations of the VHI at the Three Time Points and Cohen’s d and Effect Size Correlation r of the VHI at the Three Time Point Comparisons Time Point 1 2 3 Time Point Comparisons B–M M–E B–E
Mean VHI
Standard Deviation
11.29 6.57 4.71
1.63 1.69 1.73
Cohen’s d
Effect Size r
2.82 1.14 3.95
0.82 0.48 0.89
Abbreviations: B–M, baseline to middle of the semester; M–E, middle of the semester to end of the semester; B–E, baseline to end of the semester. 1, Baseline; 2, middle of the semester; 3, end of the semester
Although there appeared to be a consistency between the subjective and objective voice measures, inconsistencies were also observed. At the middle of the semester, many participants reported a stronger voice and positive adaptation to vocal demands with a decrease in the VHI score, whereas various objective measures and the participant self-ratings of vocal quality reflected negative changes in voice. Consequently, the participants’ perceptions that they were successful in adapting to the vocal demands combined with negative changes in subjective and objective voice measures suggest that they developed a possible false sense of vocal function, which may potentially represent a risk for developing voice problems in the future when the vocal mechanism needs to adapt to increased vocal demands as it did during the middle of the semester. It should be noted that the VHI was designed for patients with voice disorders. The participants in the present study did not have diagnosed voice disorders. The VHI was used to capture any quality-of-life changes related to voice throughout the semester of student teaching. For the VHI, the effect sizes were 0.82 and 0.89 from baseline to the middle of the semester and from baseline to the end of the semester, respectively, indicating a large clinical difference at middle and end of the semester as compared with baseline. In addition to the overall trend of the subjective and objective results, a different trend was noted with one participant. The other six participants subjectively noted voice changes across the semester, whereas one participant perceived relative consistency in her voice across the semester. At baseline, this participant noted that she was a singer and, consequently, had received voice training; therefore, it is interesting to consider that student teachers who have had exposure to voice training may adapt faster to increased vocal demands. Because it appeared that voice training allowed this participant to adapt to vocal demands more effectively and efficiently, perhaps, it may be beneficial to provide all student teachers with voice training before their student teaching experience.9 The third experimental question explored the extent to which vocal quality and vocal fatigue impacted the participants’
teaching ability. Collectively, at the middle and the end of the semester, all seven participants reported that their vocal quality and vocal fatigue were not negatively affecting their ability to teach. The lack of impact of the voice changes over the course of the semester on the participants’ teaching ability was consistent with the continual improvement that was noted on the VHI at the middle and the end of the semester. Although the participants did experience vocal quality issues and vocal fatigue, especially at the middle of the semester, the impact was not significant enough to prompt changes in their teaching ability or quality of life. It should be noted that the participants were not specifically asked if they adapted lesson plans to save their voices throughout the semester of student teaching. Perhaps, we can assume that the participants did not feel it was necessary to change teaching methods to conserve their voice, because they did not report that vocal quality and vocal fatigue were affecting their teaching ability. In addition, at the end of the semester, four of the participants reported that their voice had gained stamina, become stronger, and/or adapted to the vocal demands of teaching physical education. Future research directions The present study investigated the subjective and objective voice characteristics of female physical education student teachers during a semester of student teaching using a small participant number and a short time frame over a semester (ie, 14 weeks). Future longitudinal studies of this nature may benefit from a longer time frame to observe additional changes that may occur after the participants’ first student teaching experience. To expand the time frame and the demands on the voice, perhaps, future studies should involve the first full academic year of a beginning teacher’s career. A larger participant sample may also be beneficial to observe changes and patterns in a larger group of teachers, allowing for more detailed statistical analyses. Based on the findings discussed in the present study, vocal training before the start of student teaching may be beneficial. One participant who sang and had vocal training did not subjectively report changes in her voice over the course of the semester. A study using a control group without vocal training/ education and an experimental group with vocal training/education may provide insight into whether or not vocal training/ education would positively impact the voices of student teachers during a semester of student teaching with particular attention to the first half of the semester. This knowledge may help to prevent many of the voice problems and inappropriate vocal adaptation that the students experience during their student teaching and beyond into their professional career. Acknowledgments This study was supported by a Faculty-Student Research Award from the College of Health Sciences, West Chester University of Pennsylvania. An abbreviated version of the findings was presented at the American Speech Language Hearing Association convention in Chicago, IL, November 2008 and at the 38th Symposium: Care of the Professional Voice in Philadelphia, PA, June 2009. The authors thank Mr. Neil Szuminsky for
Elizabeth U. Grillo and Justine Fugowski
Voice Characteristics of Student Teachers
building the Global Voice Analyzer and Dr. David Bolton for his help with statistical analysis. REFERENCES 1. Roy N, Merrill RM, Thibeault S, Parsa RA, Gray SD, Smith EM. Prevalence of voice disorders in teachers and the general population. J Speech Lang Hear Res. 2004;47:281–293. 2. Smith E, Gray SD, Dove H, Kirchner L, Heras H. Frequency and effects of teachers’ voice problems. J Voice. 1997;11:81–87. 3. Smith E, Lemke J, Taylor M, Kirchner HL, Hoffman H. Frequency of voice problems among teachers and other occupations. J Voice. 1998;12:480– 488. 4. Thomas G, de Jong FICRS, Kooijman PGC, Donders ART, Cremers CWRJ. Voice complaints risk factors for voice problems and history of voice problems in relation to puberty in female student teachers. Folia Phoniatr Logop. 2006;58:305–322. 5. Russell A, Oates J, Greenwood KM. Prevalence of voice problems in teachers. J Voice. 1998;12:467–479. 6. Smith E, Kirchner HL, Taylor M, Hoffman H, Lemke JH. Voice problems among teachers: differences by gender and teaching characteristics. J Voice. 1998;12:328–334. 7. Kooijman PGC, de Jong FICRS, Thomas G, Huinck W, Donders R, Graamans K, Schutte HK. Risk factors for voice problems in teachers. Folia Phoniatr Logop. 2006;58:159–174. 8. Simberg S, Sala E, Vehmas K, Laine A. Changes in the prevalence in vocal symptoms among teachers during a twelve-year period. J Voice. 2005;19: 95–102. 9. Schneider B, Bigenzahn W. How we do it: voice therapy to improve vocal constitution and endurance in female student teachers. Clin Otolaryngol. 2005;30:64–78. 10. Niebudek-Bogusz E, Kotylo P, Sliwin´ska-Kowalska M. Evaluation of voice acoustic parameters related to the vocal-loading test in professionally active teachers with dysphonia. Int J Occup Med Environ Health. 2007;20:25–30. 11. Niebudek-Bogusz E, Fiszer M, Kotylo P, Sliwin´ska-Kowalska M. Diagnostic value of voice acoustic analysis in assessment of occupation voice pathologies in teachers. Logoped Phoniatr Vocol. 2006;31:100–106. 12. Rantala L, Vilkman E. Relationship between subjective voice complaints and acoustic parameters in female teachers’ voices. J Voice. 1999;13:484–495. 13. 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.
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14. Stemple JC, Stanley J, Lee L. Objective measures of voice production in normal subjects following prolonged voice use. J Voice. 1995;9:127–133. 15. S´liwin´ska-Kowalska M, Niebudek-Bosuz E, Fiszer M, Los-Spychalska T, Kotylo P, Sznurowska-Przygocka B, Modrzewska M. The prevalence and risk factors for occupational voice disorders in teachers. Folia Phoniatr Logop. 2006;58:85–101. 16. Jacobson BH, Johnson A, Grywalski C, Silbergleit A, Jacobson F, Benninger MS, Newman CW. The voice handicap index (VHI): development and validation. Am J Speech Lang Pathol. 1997;6:66–70. 17. Fant G. Acoustic Theory of Speech Production. The Hague, The Netherlands: Mouton; 1960. 18. Holmberg EB, Hillman RE, Perkell JS. Glottal airflow and transglottal air pressure measurements for male and female speakers in soft, normal, and loud voice. J Acoust Soc Am. 1988;84:511–529. 19. Smitheran JR, Hixon TJ. A clinical method for estimating laryngeal airway resistance during vowel production. J Speech Hear Res. 1981;46:138–146. 20. Carding PN, Steen IN, Webb A, Mackenzie K, Deary IJ, Wilson JA. The reliability and sensitivity to change of acoustic measures of voice quality. Clin Otolaryngol. 2004;29:538–544. 21. Ferrand C. Effects of practice with and without knowledge of results in jitter and shimmer levels in normally speaking women. J Voice. 1995;9:419–423. 22. Jafari M, Till J, Truesdell L, Law-Till C. Time-shift, trials and gender effects on vocal perturbation measurements. J Voice. 1993;7:326–336. 23. Sorensen D, Horii Y. Frequency and amplitude perturbation in the voices of female speakers. J Commun Disord. 1983;16:57–61. 24. Grillo EU, Perta K, Smith L. Laryngeal resistance distinguished pressed, normal, and breathy voice in vocally untrained females. Logoped Phoniatr Vocol. 2009;34:43–48. 25. Grillo EU, Verdolini K. Evidence for distinguishing pressed, normal, resonant, and breathy voice qualities by laryngeal resistance and vocal efficiency in vocally trained subjects. J Voice. 2008;22:546–552. 26. Adi-Japha E, Karni A, Parns A, Loewenschuss I, Vakil E. A shift in task routines during the learning of a motor skill: group-averaged data may mask critical phases in the individuals’ acquisition of skilled performance. J Exp Psychol Learn Mem Cogn. 2008;34:1544–1551. 27. Klaiman E, Karniel A. Bimanual adaptation: internal representations of bimanual rhythmic movements. Exp Brain Res. 2006;171:204–214. 28. Wilson C, Simpson SE, van Emmerik RE, Hamill J. Coordination variability and skill development in expert triple jumpers. Sports Biomech. 2008;7: 2–9. 29. Lai Q, Shea CH, Wulf G, Wright DL. Optimizing generalized motor program and parameter learning. Res Q Exerc Sport. 2000;71:10–24.
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Appendix A. Vocal Quality Self-Rating Scale
Appendix B. Vocal Fatigue Self-Rating Scale
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Appendix C. End-of-Semester Questionnaire
Appendix D. Order of Procedures 1. 2. 3. 4.
Consent form (at baseline time point) Screening (at baseline time point) Informal interview End-of-semester questionnaire (at end of semester time point) 5. Maximum phonation time (sustained /a/ averaged across three trials)* 6. Self-rating scale of vocal quality
7. Voice Handicap Index 8. Maximum duration time for /s/ (averaged across three trials)* 9. Self-rating scale of vocal fatigue 10. Sustained /a/ for acoustic measures held for 3 seconds in typical speaking voice 11. Maximum duration time for /z/ (averaged across three trials)* 12. Repeated /pi/s for aerodynamic measures
*The sustained duration measures of /a/, /s/, and /z/ were collected in between other measures to reduce the effects of fatigue.
INTRODUCTION Research has provided insight into the prevalence of voice disorders in teachers.1–8 Results of the research indicate that between 15% and 32% of teachers reported experiencing a voice disorder in their teaching career.1–3 Teachers were also more likely to report vocal problems and physical discomfort associated with a vocal disorder as compared with the nonteacher population.2 Additionally, student teachers, who primarily comprise young individuals at the beginning of their careers, reported a high prevalence of voice complaints.4 Female teachers were also more likely to report voice problems during their teaching careers than male teachers.5 In fact, the prevalence of voice disorders in male teachers is 13% as compared with 22% in female teachers; therefore, perhaps the female gender can be considered as a risk factor for the development of voice disorders in teachers.5 The literature also contains studies that have investigated the relationship of the subject taught and the role of age and the length of years of teaching on the voices of teachers.2,5–8 Results suggest that physical education teachers are at a higher risk for reporting voice disorders.6 In fact, 41% of the physical education teachers who participated in the study reported a voice problem.6 Researchers and clinicians have hypothesized that yelling over long distances or for long durations without amplification might contribute to the voice difficulties reported by physical education teachers.6 Research investigating the influence of age and length of teaching career on the voices of teachers has been inconclusive with mixed findings.2,5–8 Smith et al6 investigated the age and years of teaching and found no association between the two factors. Conversely, another study by Smith et al2 found that the number of vocal problems reported by teachers increased with age and the number of years of employment. Other studies conducted by Kooijman et al7 and Simberg et al8 found no relationship between the number Accepted for publication December 7, 2009. From the Department of Communicative Disorders, College of Health Sciences, West Chester University, West Chester, Pennsylvania. Address correspondence and reprint requests to Elizabeth U. Grillo, Department of Communicative Disorders, West Chester University, 201 Carter Drive, West Chester, PA 19383. E-mail: [email protected] Journal of Voice, Vol. 25, No. 3, pp. e149-e157 0892-1997/$36.00 Ó 2011 The Voice Foundation doi:10.1016/j.jvoice.2009.12.001
of teaching years and the prevalence of voice disorders in teachers. In another study, a higher prevalence of voice disorders was found in teachers between the ages of 31 and 40 years, but no significant relationship was found between the duration that the teachers had been employed and the prevalence of a voice disorder.5 Based on the contradictory findings presented previously, it is not clear if age and length of employment play a role in the prevalence of voice disorders in teachers. Researchers have not focused on the prevalence of voice disorders in student teachers, perhaps, because there is no clear evidence that voice disorders have an onset because of age or duration of years of teaching. Consequently, minimal research has been conducted concerning voice disorders among student teachers.4,9 Most of the literature has predominantly focused on the prevalence of voice disorders in teachers through survey research.1–8 However, there are some experimental studies that have provided laryngostroboscopic, acoustic, and perceptual data in both teachers and student teachers.9–14 Stroboscopic data revealed irregular vocal fold vibrations, incomplete glottal closure, and soft vocal nodules as a baseline vocal fold pattern in teachers.10 Acoustic measures collected after vocal loading demonstrated an increase in fundamental frequency (F0), jitter, relative average perturbation, shimmer, and amplitude perturbation among teachers and nonteachers.10–14 After vocal loading, teachers and nonteachers demonstrated deterioration in mucosal wave propagation and incomplete glottal closure.11,14 One study demonstrated that student teachers who participated in voice therapy and vocal hygiene education had improved jitter, shimmer, F0, and glottal closure,9 therefore, supporting a voice disorders prevention paradigm at the training level of student teachers. Although this body of research has provided insight into the prevalence of voice disorders in teachers and some objective voice data among teachers, further work is required to assess the impact of teaching on the voices of student teachers. Only one study has investigated acoustic, laryngostroboscopic, and perceptual voice measures in student teachers, but no study to date has focused on female physical education student teachers.9 It is important to consider female student teachers, because female teachers are at a higher risk for developing a voice disorder.5 In addition, much of the research has not
e150 assessed the effect of the subject taught on the voices of teachers and student teachers. Physical education teachers had a higher probability of reporting voice difficulties; therefore, teaching physical education might be considered a risk factor for developing a voice disorder.6 Most of the research focused on a series of continuous days or several time points within the day but failed to provide objective information on voice characteristics over the course of weeks or months. Conducting research in a longitudinal manner will provide a more accurate representation of what happens to the voices of student teachers during their student-teaching experience. Based on the high prevalence of voice disorders in the teaching profession, a prevention paradigm should be developed to minimize the likelihood of developing a voice disorder. The literature emphasizes the need for vocal education in the teaching profession.7,15 Because the teaching profession is at such a high risk for developing voice problems, teachers should be educated on how to compensate for the voice demands of their occupation.2 This voice disorder prevention paradigm for teachers must begin at the training level in the education of student teachers. With the goal of developing such a prevention paradigm beginning at the training level, it must be understood and evaluated what happens to the voices of student teachers during a semester of student teaching. Considering the gaps in the literature, the purpose of this study was to investigate the subjective and objective voice characteristics of female physical education student teachers during a semester of student teaching. The specific research questions were (1) will the subjective and objective voice measures of female physical education student teachers change during the semester of student teaching; (2) will the changes be consistent across the subjective and objective voice measures; and (3) will vocal quality and/or vocal fatigue impact the student teachers’ teaching abilities during the semester? METHODS Participants The participants, comprised of seven female physical education student teachers, enrolled in the undergraduate teacher education program at West Chester University in West Chester, Pennsylvania. One participant was a singer. Females were chosen because of the high prevalence of voice disorders among female teachers.5 Physical education teachers were more likely than teachers who taught other disciplines to report voice disorders6; therefore, physical education student teachers participated in the study. The physical education student teachers completed their 14-week student teaching semester at both the primary education level (ie, elementary school) and the secondary education level (ie, high school), spending 7 weeks at each level. A typical school day consisted of 7–8 hours of talking in physical education or health classes in large gymnasiums or classrooms. After informed consent, participants completed screening procedures. The screening consisted of a questionnaire and a puretone hearing screening at 20 dB for the following frequencies: 500, 1000, 2000, and 4000 Hz. The inclusion criteria were as follows: female gender, ages 20–25 years, physical education student teacher, first semester of student teaching, normal
Journal of Voice, Vol. 25, No. 3, 2011
hearing as determined by passing the pure-tone hearing screening, and no current voice problem. If the participants met the inclusion criteria, they were enrolled in the study. After enrollment in the study, participants were required to complete the collection of voice data at three time points in the semester. The first time point for data collection occurred before the participants began their first semester of student teaching immediately after screening procedures on a week day during the semester break between fall and spring semesters (ie, baseline). Participants returned midway through the semester after a full day of teaching to collect data for the second time point approximately 7 weeks after baseline (ie, middle of the semester). The third time point occurred at the conclusion of the participants’ student teaching practicum semester after a full day of teaching approximately 7 weeks after the middle of the semester (ie, end of the semester). All measures collected during the first time point served as each participant’s baseline for later comparison with the second and third time points. The participants also completed an informal interview at baseline, middle of the semester, and end of the semester inquiring about their student teaching experience and their voice production. Instruments Several subjective and objective measures were administered at three data collection time points throughout the semester of student teaching. For the subjective measures, self-rating scales of vocal quality and vocal fatigue were given to the participants along with the end-of-semester questionnaire and the Voice Handicap Index (VHI)16 (Appendices A–C). The subjective measures were completed by the participants. The objective measures included acoustic and aerodynamic data. Acoustic measurements were collected by the experimenter using the Multidimensional Voice Program software program by KayPentax (Lincoln Park, NJ) on a Dell desktop computer using a head-mounted microphone (AKG with a frequency response of 20–20 000 Hz and sensitivity at 1000 Hz of 7 mV/Pa) 3 inches from the mouth. Various acoustic measurements were elicited from sustained phonation of /a/ for 3 seconds in a typical speaking voice for each data collection time point. From sustained phonation, the acoustic measures of F0, absolute jitter, and percent shimmer were collected. Sustained phonation of /a/ was used, because it involves a relatively open vocal tract with limited oral-pharyngeal constriction, whereas connected speech involves dynamic changes between open vocal tract for vowels and very constricted oral-pharyngeal patterns for different types of consonants.17 As a result, a more accurate representation of vocal fold vibration can be observed with measures collected during sustained phonation because of the lack of articulator interference. Absolute jitter and percent shimmer were selected for the study, because they are based on differences between successive periods or amplitudes of the speaker’s F0 and sound pressure level, respectively. In addition, to be consistent with previous studies that assessed changes in jitter and shimmer measures of student teachers who underwent voice therapy9 and of teachers pre- and post-vocal loading10–14 absolute jitter and percent shimmer were selected for the present study. Aerodynamic data were captured using the Global Voice Analyzer, which includes a circumferentially vented face mask
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Voice Characteristics of Student Teachers
with attached airflow (model number 1Inch-D-4V) and pressure (model number 10Inch-D-4V) transducers, manufactured by All Sensors (Morgan Hill, CA). The airflow-measurement equipment was calibrated for aerodynamic functions before each day’s data collection using a Dwyer (Michigan City, IN) U tube manometer for pressure and a Glottal Enterprises (Syracuse, NY) pneumotach calibration unit for airflow. Participants placed a vented mask over their mouth and nose, while positioning plastic tubing intraorally connected to the pressure transducer, avoiding blockage of the tube by the tongue. A strap was placed around the participant’s head and tightened to secure a tight seal with the participant’s face. After the experimenter checked the mask positioning to verify the seal, the participant was trained to produce a five-syllable consonant-vowel syllable string (/pi pi pi pi pi/) repeated three times at an approximate rate of 88 beats per minute in a typical speaking voice.18 A metronome was used to provide the beat pattern (88 beats per minute) for production of consonant/vowel strings (/pi/). Subglottic pressures (Ps) were estimated from oral pressures for each trial using software that obtained the interpolated pressure between pressure peaks two and three, three and four, and four and five for each /pi pi pi pi pi/ string as well as the time-locked average airflow for those syllables.18 Laryngeal resistance (ie, LR: Ps divided by average airflow, cm H2O/L/s19) was calculated from the combination of the estimated Ps and subsequent average airflow. Summary files were generated by the software program that indicated Ps, airflow, and LR. Maximum phonation time (MPT) during sustained /a/ and the s/z ratio were also captured and averaged across three trials for each data collection time point. MPT and the s/z ratio were collected because they provide information related to the balance of airflow with phonation, do not require instrumentation, and therefore, are typical clinical measures. With the exception of the consent form, screening procedures, and the end-of-semester questionnaire, the same methods and order of procedures were used in each of the three data collection sessions (Appendix D). Because of the small participant number, descriptive analyses were chosen to represent the results most effectively. Cohen’s d and the effect size correlation r were used to measure the strength of the relationship between two variables. Cohen’s d was calculated as the difference between the means divided by a standard deviation. The equation used for Cohen’s d was d ¼ x1 x2 s with s defined as sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðn1 1Þs21 þ ðn2 1Þs22 : s¼ n1 þn Cohen’s d was calculated three times for each of the numerical dependent variables comparing baseline with middle of the semester, middle of the semester with end of the semester, and baseline with end of the semester. The effect size correlation r was also computed from Cohen’s d for each of the numerical dependent variables across the time point comparisons.
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RESULTS Acoustic measures The means and standard deviations of F0, absolute jitter, and percent shimmer during sustained phonation of /a/ were collected at three time points: baseline, middle, and end of the semester of student teaching (Table 1). Compared with baseline for each of the seven participants, the means and standard deviations of F0, absolute jitter, and percent shimmer increased at the middle and the end of the semester. Cohen’s d and the effect size correlation r, at the three time point comparisons for F0, absolute jitter, and percent shimmer, demonstrated effect sizes ranging from small (ie, 0.1–0.3) to medium (ie, 0.5) (Table 2). Aerodynamic measures The means and standard deviations of LR, Ps, and average airflow were calculated at each of the time points from three repetitions of /pi pi pi pi pi/ for a total of 15 /pi/s (Table 3). Mean LR decreased from baseline at the middle of the semester and then increased from baseline at the end of the semester. Collectively, the mean Ps increased at the middle and the end of the semester as compared with that at baseline. The mean airflow rate increased from baseline at the middle of the semester and then decreased at the end of the semester but did not return to baseline. The means and standard deviations of MPT and the s/z ratio were calculated at each time point (Table 3). Overall, the MPT decreased from baseline at the middle of the semester and then increased at the end of the semester but did not exceed the baseline value. Overall, the mean s/z ratio increased from baseline at the middle of the semester and at the end of the semester. Cohen’s d and the effect size correlation r, at the three time point comparisons for LR, Ps, average airflow, MPT, and the s/z ratio, demonstrated effect sizes ranging from small to large (ie, 0.8) (Table 4). Participant rating scales The participants were asked to evaluate their vocal quality and vocal fatigue by completing the self-rating scales at each of the three data collection time points (Appendices A and B). All ratings involving pitch and loudness remained consistent throughout the semester. For example, at baseline, middle, and end of the semester, six participants reported that pitch was ‘‘just right,’’ and one participant reported that pitch was ‘‘too low.’’ For loudness, at baseline, middle, and end of the semester, six of the participants reported that loudness was ‘‘just right,’’ and one participant reported that loudness was ‘‘too loud.’’ Additionally, the participants rated overall vocal quality and vocal fatigue. At the baseline time point, all seven participants rated their voice as sounding ‘‘clear’’ and three of the seven participants reported experiencing vocal fatigue ‘‘sometimes.’’ By the middle of the semester, six participants reported negative voice quality changes. Specifically, three participants reported a ‘‘hoarse’’ voice, and three participants reported a ‘‘strained or raspy’’ voice at the middle of the semester. At the middle of the semester interview, two of the seven participants reported ‘‘voice loss’’ for the first few weeks of the semester. Related to vocal fatigue, six participants reported experiencing vocal
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TABLE 1. Means and Standard Deviations of F0, Absolute Jitter, and Percent Shimmer During Sustained Phonation of /a/ at the Three Time Points
TABLE 2. Cohen’s d and Effect Size Correlation r of F0, Absolute Jitter, and Percent Shimmer During Sustained Phonation of /a/ at the Three Time Point Comparisons
Acoustic Measure
Acoustic Measure
Time Point
Mean
Standard Deviation
F0 (Hz)
1 2 3
195.38 198.98 208.91
8.11 11.09 15.24
Absolute jitter
1 2 3
41.09 43.07 51.34
9.45 11.96 16.76
Percent shimmer
1 2 3
2.63 3.02 3.19
0.17 0.32 0.60
1, Baseline; 2, middle of the semester; 3, end of the semester.
fatigue by the middle of the semester ‘‘sometimes,’’ which is a 50% increase from baseline. Although six participants reported negative voice quality changes and an increase in vocal fatigue at the middle of the semester, all six participants reported that they were successful in adapting to the vocal demands of teaching. By the end of the semester, voice quality ratings improved, whereas vocal fatigue ratings remained the same from the middle of the semester. For voice quality, six participants rated their voice as ‘‘clear,’’ and one participant rated her voice as ‘‘hoarse’’ by the end of the semester. At both the middle and the end-of-semester time points, all seven participants reported that their vocal quality and vocal fatigue were not affecting their teaching ability. At the conclusion of subjective and objective data collection at the end of the semester, the participants were administered the end-of-semester questionnaire to gain additional information about their vocal quality and student teaching experiences (Appendix C). The participants were asked to compare their vocal quality at the end of the semester with that at baseline. All of the seven participants reported that their vocal quality was not worse at the end of the semester as compared with that at baseline, but six participants reported that their vocal quality was different at the end of the semester as compared with that at baseline. Out of the six participants who responded that their vocal quality was different, four participants reported that their voice had become stronger, gained stamina, and/or adapted to vocal demands. Additionally, two participants reported a strained, scratchy, lower-pitched voice at the end of the semester as compared with that at baseline. The participants also compared their vocal fatigue at the end of the semester with that at baseline. Five participants reported that they did not feel increased vocal fatigue at the end of the semester as compared with that at baseline. Two participants reported that they did experience increased vocal fatigue at the end of the semester as compared with that at baseline. Participants also completed the VHI at all three time points. Overall, compared the baseline value for each of the seven participants, the VHI value decreased both at the middle and the end of the semester
Time Point Comparisons
Cohen’s d
Effect Size r
F0 (Hz)
B–M M–E B–E
1.12 0.37 0.75
0.48 0.18 0.35
Absolute jitter
B–M M–E B–E
0.18 0.56 0.75
0.09 0.27 0.35
Percent shimmer
B–M M–E B–E
1.54 0.35 1.35
0.61 0.17 0.54
Abbreviations: B–M, baseline to middle of the semester; M–E, middle of the semester to end of the semester; B–E, baseline to end of the semester
(Table 5). In addition, Cohen’s d and the effect size correlation r for the VHI indicated a negative change from baseline at the middle and the end of the semester, ranging from a medium to a large effect size. DISCUSSION The first two experimental questions investigated the extent to which the subjective and objective measures of the participants’ voices changed during a semester of student teaching and whether or not the changes were consistent across the subjective and objective voice measures. Based on the analysis of the results, it is clear that the subjective and objective voice parameters of the student teachers changed across the semester. Related to acoustics, the means and standard deviations of F0, absolute jitter, and percent shimmer increased at the middle and the end of the semester as compared with those at baseline, possibly indicating an increase in variability of vocal fold vibration as the voice demands of the student teachers increased throughout the semester of student teaching. Changes noted in the acoustic measures at the middle of the semester also coincided with the subjective difficulties noted by the participants. In the present study, considering the intense voice demands for student teaching across the semester, the increases observed in F0, absolute jitter, and percent shimmer were consistent with the results of previous research immediately after vocal loading.10–14 For the acoustic measures, the effect sizes ranged from 0.09 to 0.61, indicating a small to medium clinical difference among the baseline, middle, and end of the semester time points. This finding was possibly because of the variability in the acoustic measures. For example, Carding et al20 reported poor to moderate retest reliability and poor sensitivity to change for jitter and shimmer measures. In addition, reported normative values of jitter and shimmer vary considerably among studies,21–23 thus suggesting the highly variable nature of jitter and shimmer measures. Changes were also noted throughout the semester for the aerodynamic measures of LR, Ps, airflow, MPT, and the s/z ratio.
Elizabeth U. Grillo and Justine Fugowski
TABLE 3. Means and Standard Deviations of LR, Ps, Airflow, MPT, and the s/z Ratio at the Three Time Points Aerodynamic Measure LR (cm H2O/L/s)
Ps (cm H2O)
Airflow (mL/s)
MPT (s)
s/z Ratio
Time Point
Mean
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Standard Deviation
TABLE 4. Cohen’s d and Effect Size Correlation r of LR, Ps, Airflow, MPT, and the s/z Ratio at the Three Time Point Comparisons Aerodynamic Measure
Time Point Comparisons
Cohen’s d
Effect Size r
LR (cm H2O/L/s)
B–M M–E B–E
1.22 1.13 0.21
0.53 0.49 0.10
Ps (cm H2O)
B–M M–E B–E
0.92 1.65 2.54
0.42 0.63 0.78
Airflow (mL/s)
B–M M–E B–E
2.43 1.32 0.97
0.77 0.54 0.43
1 2 3
16.51 14.29 17.05
2.03 1.50 3.09
1 2 3
3.01 3.18 3.48
0.19 0.18 0.19
1 2 3
209.04 277.00 237.57
26.66 29.46 32.16
1 2 3
20.33 18.80 19.23
2.64 2.02 2.34
MPT (s)
1 2 3
1.15 1.22 1.90
0.19 0.19 0.13
B–M M–E B–E
0.65 0.19 0.50
0.31 0.09 0.24
s/z Ratio
B–M M–E B–E
0.37 4.25 4.67
0.18 0.90 0.92
1, Baseline; 2, middle of the semester; 3, end of the semester.
B–M, baseline to middle of the semester; M–E, middle of the semester to end of the semester; B–E, baseline to end of the semester.
The fluctuation of the mean LR values can possibly be a result of adaptation to increased vocal demands throughout the semester of student teaching. Specifically, the decrease in LR at the middle of the semester was consistent with the changes in other objective measures and also with subjective comments of the participants that a period of voice change occurred at the middle of the semester. The voice change, at the middle of the semester, was characterized by six of the participants as ‘‘hoarse or strained/raspy,’’ suggestive of decreased resistance to the flow of air, possibly because of incomplete glottal closure.11,14,24,25 The consecutive increase of the mean Ps at the middle and the end of the semester can possibly be attributed to compensation techniques developed by the student teachers to produce a louder vocal quality as the semester of student teaching progressed.18 The fluctuation of mean airflow rates across the semester can possibly be because of the participants’ vocal folds adapting to increased vocal demands throughout the semester of student teaching. Specifically, the increase in mean airflow rate at the middle of the semester might indicate an incomplete glottal closure pattern as seen in previous research after vocal loading in teachers and nonteachers.11,14 The trend in MPT and the s/z ratio was also consistent with LR, mean airflow rates, and subjective comments of the participants. Specifically, at the middle of the semester, MPT and the /z/ portion of the s/z ratio were not as long as those at baseline, possibly indicating difficulties in coordinating respiration with vocal fold vibration because of incomplete glottal closure.11,14 For the aerodynamic measures, the effect sizes ranged from 0.09 to 0.92, with some effects demonstrating a change in the negative direction, indicating a decrease in the numerical value of the dependent variable. The magnitude of the clinical difference ranged from small to large depending on the aerodynamic measure.
Much like the objective measures, several subjective measures changed from baseline at the middle and the end of the semester; for example, an increase in the number of participants who experienced vocal fatigue and who reported negative changes in vocal quality was noted at the middle of the semester. By the end of the semester, however, some of the subjective and objective measures demonstrated closer approximations to baseline levels; for example, better coordination of respiration during phonation (eg, MPT) and a decrease in the number of participants who reported negative voice quality changes. The voice changes, at the middle of the semester, could be attributed to the vocal mechanism negatively reacting to the new skill of increased vocal demands necessary for teaching physical education. Conversely, at the end of the semester, the improvements in voice, closer to baseline levels, might be suggestive of the vocal mechanism adapting positively to the vocal demands of teaching physical education as the newly learned skill was stabilized. A similar trend has been documented in the motor learning literature, where a negative practice effect can occur characterized by a period of increased errors when learning a new skill.26–29 After this period of increased errors, the errors decrease as the newly learned skill is stabilized.26–29 The end goal of the participants was to learn a new voice pattern for the increased vocal demands of teaching physical education. At the middle of the semester, the participants were possibly experiencing a negative practice effect as evidenced by the change in subjective and objective voice measures from baseline. By the end of the semester, the new voice pattern was stabilized, as evidenced by most of the subjective and objective voice measures returning closer to those at baseline levels.
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TABLE 5. Means and Standard Deviations of the VHI at the Three Time Points and Cohen’s d and Effect Size Correlation r of the VHI at the Three Time Point Comparisons Time Point 1 2 3 Time Point Comparisons B–M M–E B–E
Mean VHI
Standard Deviation
11.29 6.57 4.71
1.63 1.69 1.73
Cohen’s d
Effect Size r
2.82 1.14 3.95
0.82 0.48 0.89
Abbreviations: B–M, baseline to middle of the semester; M–E, middle of the semester to end of the semester; B–E, baseline to end of the semester. 1, Baseline; 2, middle of the semester; 3, end of the semester
Although there appeared to be a consistency between the subjective and objective voice measures, inconsistencies were also observed. At the middle of the semester, many participants reported a stronger voice and positive adaptation to vocal demands with a decrease in the VHI score, whereas various objective measures and the participant self-ratings of vocal quality reflected negative changes in voice. Consequently, the participants’ perceptions that they were successful in adapting to the vocal demands combined with negative changes in subjective and objective voice measures suggest that they developed a possible false sense of vocal function, which may potentially represent a risk for developing voice problems in the future when the vocal mechanism needs to adapt to increased vocal demands as it did during the middle of the semester. It should be noted that the VHI was designed for patients with voice disorders. The participants in the present study did not have diagnosed voice disorders. The VHI was used to capture any quality-of-life changes related to voice throughout the semester of student teaching. For the VHI, the effect sizes were 0.82 and 0.89 from baseline to the middle of the semester and from baseline to the end of the semester, respectively, indicating a large clinical difference at middle and end of the semester as compared with baseline. In addition to the overall trend of the subjective and objective results, a different trend was noted with one participant. The other six participants subjectively noted voice changes across the semester, whereas one participant perceived relative consistency in her voice across the semester. At baseline, this participant noted that she was a singer and, consequently, had received voice training; therefore, it is interesting to consider that student teachers who have had exposure to voice training may adapt faster to increased vocal demands. Because it appeared that voice training allowed this participant to adapt to vocal demands more effectively and efficiently, perhaps, it may be beneficial to provide all student teachers with voice training before their student teaching experience.9 The third experimental question explored the extent to which vocal quality and vocal fatigue impacted the participants’
teaching ability. Collectively, at the middle and the end of the semester, all seven participants reported that their vocal quality and vocal fatigue were not negatively affecting their ability to teach. The lack of impact of the voice changes over the course of the semester on the participants’ teaching ability was consistent with the continual improvement that was noted on the VHI at the middle and the end of the semester. Although the participants did experience vocal quality issues and vocal fatigue, especially at the middle of the semester, the impact was not significant enough to prompt changes in their teaching ability or quality of life. It should be noted that the participants were not specifically asked if they adapted lesson plans to save their voices throughout the semester of student teaching. Perhaps, we can assume that the participants did not feel it was necessary to change teaching methods to conserve their voice, because they did not report that vocal quality and vocal fatigue were affecting their teaching ability. In addition, at the end of the semester, four of the participants reported that their voice had gained stamina, become stronger, and/or adapted to the vocal demands of teaching physical education. Future research directions The present study investigated the subjective and objective voice characteristics of female physical education student teachers during a semester of student teaching using a small participant number and a short time frame over a semester (ie, 14 weeks). Future longitudinal studies of this nature may benefit from a longer time frame to observe additional changes that may occur after the participants’ first student teaching experience. To expand the time frame and the demands on the voice, perhaps, future studies should involve the first full academic year of a beginning teacher’s career. A larger participant sample may also be beneficial to observe changes and patterns in a larger group of teachers, allowing for more detailed statistical analyses. Based on the findings discussed in the present study, vocal training before the start of student teaching may be beneficial. One participant who sang and had vocal training did not subjectively report changes in her voice over the course of the semester. A study using a control group without vocal training/ education and an experimental group with vocal training/education may provide insight into whether or not vocal training/ education would positively impact the voices of student teachers during a semester of student teaching with particular attention to the first half of the semester. This knowledge may help to prevent many of the voice problems and inappropriate vocal adaptation that the students experience during their student teaching and beyond into their professional career. Acknowledgments This study was supported by a Faculty-Student Research Award from the College of Health Sciences, West Chester University of Pennsylvania. An abbreviated version of the findings was presented at the American Speech Language Hearing Association convention in Chicago, IL, November 2008 and at the 38th Symposium: Care of the Professional Voice in Philadelphia, PA, June 2009. The authors thank Mr. Neil Szuminsky for
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Appendix A. Vocal Quality Self-Rating Scale
Appendix B. Vocal Fatigue Self-Rating Scale
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Appendix C. End-of-Semester Questionnaire
Appendix D. Order of Procedures 1. 2. 3. 4.
Consent form (at baseline time point) Screening (at baseline time point) Informal interview End-of-semester questionnaire (at end of semester time point) 5. Maximum phonation time (sustained /a/ averaged across three trials)* 6. Self-rating scale of vocal quality
7. Voice Handicap Index 8. Maximum duration time for /s/ (averaged across three trials)* 9. Self-rating scale of vocal fatigue 10. Sustained /a/ for acoustic measures held for 3 seconds in typical speaking voice 11. Maximum duration time for /z/ (averaged across three trials)* 12. Repeated /pi/s for aerodynamic measures
*The sustained duration measures of /a/, /s/, and /z/ were collected in between other measures to reduce the effects of fatigue.