ORIGINAL ARTICLE
Year : 2022 | Volume
: 36 | Issue : 2 | Page : 45--53
Vocal habits, dysphonia severity index, and voice-related quality of life in indian primary school teachers: An exploratory study
Zaiba Khateeb, SV Narasimhan
Department of Speech and Language Pathology, JSS Institute of Speech and Hearing, Mysore, Karnataka, India
Correspondence Address:
Dr. S V Narasimhan
Department of Speech and Language Pathology, JSS Institute of Speech and Hearing, MG Road, Mysore - 570 004, Karnataka
India
Abstract
Context: Only a handful of studies have explored the relationship between vocal habits, Dysphonia Severity Index (DSI) scores, and Voice-Related Quality of Life (VRQOL), especially among Indian primary school teachers. Aims: We aimed to document the factors affecting DSI and VRQOL scores among Indian primary school teachers and to study the correlation between these measures in Indian teachers with and without dysphonia. Settings and Design: This was a retrospective standard group comparison study. Subjects and Methods: A total of 90 primary school teachers (33 males and 57 females) were administered a vocal health questionnaire, and based on the questionnaire responses, participants were classified into two groups. Group 1 consisted of 33 participants without any self-reported symptoms of voice problems. Group 2 included 57 participants with self-reported symptoms of voice problems. Further, the phonation samples were recorded, and DSI scores were calculated. Participants were also instructed to fill out the VRQOL questionnaire. Statistical Analysis Used: Shapiro–Wilk test, the Mann–Whitney U-test, and Spearman's rank correlation coefficient were carried out as a part of statistical analyses. Results: Teachers with self-reported vocal symptoms exhibited more frequent habits such as consumption of beverages, intake of spicy and oily food, less time interval between intake of meals and sleep, coughing, speaking at uncomfortable volumes, and frequent screaming or yelling or cheering. There was a significant positive correlation between VRQOL and the DSI values. Conclusion: Future studies can be carried out to discern the impact of the classroom's size, population, background noise, and amplification equipment on teachers.
How to cite this article:
Khateeb Z, Narasimhan S V. Vocal habits, dysphonia severity index, and voice-related quality of life in indian primary school teachers: An exploratory study.J Indian Speech Language Hearing Assoc 2022;36:45-53
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Khateeb Z, Narasimhan S V. Vocal habits, dysphonia severity index, and voice-related quality of life in indian primary school teachers: An exploratory study. J Indian Speech Language Hearing Assoc [serial online] 2022 [cited 2023 Apr 1 ];36:45-53
Available from: https://www.jisha.org/text.asp?2022/36/2/45/367505 |
Full Text
Introduction
Individuals whose livelihood depends on effective vocal communication are called occupational/professional voice users.[1] The professional and economic well-being of these occupational voice users depends on their normal vocal function and voice endurance.[2],[3] Teachers form a larger part of occupational voice users and depend highly on their voice for their occupation.[1] Even though an average vocal capacity is adequate for most occupational voice users, some specific occupational voice users, such as teachers, require exceptional vocal endurance and a high degree of vocal capacity beyond the needs of everyday speaking.[4] Teachers are considered at an increased risk of voice disorders due to their loud and continuous voice usage[5] in combination with exposure to some environmental factors such as prolonged and continuous hours of teaching, poor classroom acoustics, and the deficient student–teacher ratio.[6]
Voice disorder or dysphonia refers to the deviations in pitch, quality, flexibility, or loudness of one's voice that are inappropriate for an individual's gender, age, geographical location, or cultural background.[7] Dysphonia can cause impairment or limit vocal activity due to functional or structural deviations in the laryngeal system.[8] Normal voice production requires a delicate balance between the vocal fold movement and the laryngeal airflow through the glottis.[9] However, in a laryngeal pathology or dysphonia, this delicate balance between the airflow in the glottis and the vocal fold movement is negatively affected,[10],[11] thereby altering vocal pitch, quality, or loudness.
There are various ways to assess voice quality in dysphonia.[12] Even though the medical diagnosis of laryngeal pathology is majorly based on laryngeal visualization procedures such as endoscopy, vocal dysfunction is commonly assessed using subjective or objective methods.[13] Subjective assessment includes perceptual analysis of voice with clinical-based assessments or the client self-report assessments, and instrumental or objective evaluation of voice using acoustic analysis, aerodynamic analysis, and cepstral and spectral analyses of voice. Both perceptual and objective measures of voice have their benefits and limitations as well.[12],[14] However, the literature review on voice research indicates no consensus about a sensitive measure that unambiguously classifies and quantifies the dysphonic and normal voice.[13] Earlier studies have concluded that it is impossible to derive clinically potential inferences on the quality of voice based on any single variable that has low correlations with the perceptual quality of voice.[15] As the voice pathologist is frequently challenged during the evaluation of dysphonic voice due to the inconsistent association between the voice quality, vocal fold lesions, and measurement parameters in an individual with dysphonia, and there is currently no agreement on the most effective protocol, most the current studies advocate the use of multidimensional approaches.[13]
The Dysphonia Severity Index (DSI)[13] is a multidimensional approach that is a linear combination of various vocal parameters extracted through acoustic analysis, aerodynamic analysis, and voice range profile.[16] DSI was initially built based on 13 aerodynamic and acoustic parameters using the proportional odds logistic regression model. The final model included a weighted combination of four parameters – maximum phonation time, highest phonation frequency, lowest intensity, and jitter.
Voice disorders affect an individual's communication and impact emotional and social well-being.[17] As a normal voice with good vocal endurance is essential for occupational voice users such as teachers, dysphonia can affect their profession and livelihood and indirectly impact their quality of life.[18],[19] Earlier researchers have developed various subjective tools to document the impacts of voice problems on an individual's daily living and quality of life.[20] These tools include the Voice Activity and Participation Profile,[21] the Voice-Related Quality of Life (VRQOL),[20] and the Voice Handicap Index (VHI).[22] Various researchers have also used VRQOL to investigate the relationships between quality of life and current voice problems faced by people.[23] It also helps to understand the individual's perception of their voice and their present reaction to voice disorders.
As VRQOL has been a reliable subjective tool, VRQOL has been widely used to document the quality of life of patients with voice disorder/dysphonia.[17] Aghadoost et al.[24] investigated the relationship between voice complaints and the quality of life among Persian-speaking Iranian teachers. They showed that the teachers with voice complaints have a lower VRQOL. A recent study reported that primary or high school teachers from China with voice disorders/dysphonia had a significantly poorer VRQOL than those without any voice disorders.[17] The study also reported that different types and grades of voice disorders affect VRQOL scores.[17]
Some researchers have documented the relationship between the DSI scores and VRQOL, especially among individuals with voice problems, and have reported mixed results. Hummel et al.[25] investigated the relationship between objective voice measure, i.e., DSI, and the self-perception of voice handicap, i.e., VRQOL, among dysphonic patients and showed no significant correlation between VRQOL and DSI. The authors concluded that the objective voice measure and the perception of voice quality by the patient were two independent parameters.
Teachers are more likely than other voice professionals to acquire vocal disorders and report high rates of specific voice symptoms and physical discomfort when voicing.[26] Mansouri et al.[4] investigated the relationship between DSI and VRQOL in Iran's primary school teachers with voice disorders. Results revealed that teachers had a low DSI that reflected poor laryngeal function. Low DSI scores were associated with lower VRQOL, and there was a significant positive correlation between the overall scores of DSI and VRQOL. However, these studies had not attempted to explore the possible factors related to the poor DSI and VRQOL scores among the teachers, especially in India.
Investigations show that teachers have the highest rate of vocal abnormalities, which are caused by both environmental and health issues, when compared to other professional groups.[27] Sathyanarayan et al.[5] surveyed India and reported that 49% of high and higher secondary Indian school teachers have voice difficulties. Teaching at a high voice output level is dangerous due to background noise, bad classroom acoustics, poor working posture, lengthy speaking distance, poor quality of air ventilation, stress, and the lack or poor quality of assistance. Individual endurance, gender, living habits, vocal experiences, medical issues, stress, anxiety, and psychological factors are all contributing cofactors.[28] As recent studies have revealed that teachers in India are at risk of developing voice disorders due to some factors such as poor classroom acoustics, prolonged teaching hours, and the poor student–teacher ratio,[6] it is essential to document the DSI and VRQOL scores and the factors affecting DSI and VRQOL scores and to study the correlation between these measures in Indian teachers with and without dysphonia.
Subjects and Methods
Participants
The study included 90 primary school teachers (33 males and 57 females) from government Kannada- and English-medium schools in and around Mysore district, Karnataka, India, and informed written consent was obtained from all the participants. All the participants were selected after obtaining approval from the respective Block Education Officers and the Heads of the Institutions under the Government of Karnataka education at the Mysore district level. All the participants were included in the present study with an age range of 28–59 years with a mean age of 44.81 ± 7.74 years. All the participants had a minimum of 3 years of teaching experience and a minimum qualification of Teacher Certificate Higher or Bachelor of Education qualification and a maximum postgraduation qualification. All the participants had normal hearing sensitivity and no history of any speech, language, or neurological problems. None of the participants reported any hormonal-related issues, at least from the past 5 years. A convenient sampling procedure was used to select the participants in the current study.
Once the participants were selected, the vocal health questionnaire was administered to all the participants. Based on the self-reported symptoms of voice problems reported by the participants as a response to the vocal health questionnaire, the participants were classified into two groups. Group 1 consisted of 33 participants (12 males and 21 females) within the age range of 29–59 years (mean age of 45.42 ± 7.8 years) without any self-reported symptoms of voice problems. Group 2 included 57 participants (21 males and 36 females) within the age range of 28–58 years (mean age of 43.27 ± 7.31 years) with the self-reported symptom of voice problem.
Procedure
Data collection
The participants were instructed to fill vocal health questionnaire.[5] The questionnaire consisted of three sections. The first section consisted of questions related to demographic details; the second section included questions to elicit information on their general usage of voice, and the last section consisted of close-ended questions about vocal health practices. Based on the responses to the vocal health questionnaire, the participants were divided into two groups. Further, the participants of both the groups were instructed to fill out the English version of VRQOL questionnaire.[20] VRQOL questionnaire consisted of 10 questions with a 5-point rating scale, where a rating of “1” indicates “not at all problem,” and a rating of “5” indicates “problem as bad it can be.” Following the questionnaires, the voice samples of all the participants were recorded in a sound-treated room.[29] Each participant was instructed to take a deep breath and phonate the vowels/a/at their habitual pitch and comfortable loudness. Before the recording, the investigator demonstrated the maximum phonation duration of the vowel by taking a deep breath and phonating /a/for as long as possible. A unidirectional dynamic microphone was placed on the table at a constant distance of 15 cm away from the mouth of the participant. An HP Pavilion laptop with an Intel Core i7 processor loaded with Praat software (version 6.0.56)[30] was used to record the phonation sample of the participants.
Data analysis
Responses to VRQOL obtained from each participant were tabulated. The responses of each participant on the 5-point rating scale were added, and the total summed score of VRQOL was calculated. Thus, the responses of VRQOL obtained from the participants of both the groups were tabulated and subjected to statistical analysis. The acoustic parameters were extracted using PRAAT software. DSI was calculated using the formula DSI = 0.13 × MPT + 0:0053 × F0 high − 0.26 × Ilow − 1:18 × jitter + 12.4 (where F0-high [Hz] is the highest phonation frequency and Ilow is the lowest intensity), proposed in the earlier study[13] for all the participants using acoustic parameters, namely, maximum phonation time, maximum fundamental frequency, minimum intensity, and jitter PPQ.
Statistical analyses
The distribution of data was examined using the Shapiro–Wilk test. The frequency distribution of each voice-related habit was calculated for the responses to the vocal health questionnaire for the participants of both the groups. As a part of descriptive statistics, mean, median, and standard deviation values were calculated for the vocal health behaviors of the participants of both the groups. As the results of Shapiro–Wilk test showed that the data were nonnormally distributed, the Mann–Whitney U-test was carried out to check the significant difference between the participants of both the groups. Discriminant analysis was carried out to determine the set of vocal behaviors that discriminated the participants of group 1 and group 2 with all the vocal behaviors as predictor variables. Mean and standard deviation values were calculated for the DSI and VRQOL scores for the participants of both the groups. Mann–Whitney U-test was performed to check the significant difference in the DSI and VRQOL scores between the participants of group 1 and group 2. Further, Spearman's rank correlation coefficient was carried out to document the correlation between VRQOL and DSI scores among the participants of group 2. All the statistical analyses were carried out at a confidence interval of 95% using SPSS (IBM, SPSS Statistics for Windows, Version 24.0).[31]
Results
[Table 1] presents the frequency distribution of vocal health-related habits among the participants of both the groups. Among diet-related habits, it was noted that intake of caffeinated beverages and spicy and oily food was more frequent among the participants of group 2 compared to group 1. The time interval between intake of meals and sleep was observed to be shorter among participants in group 2 compared to group 1. However, there were no differences in intake of aerated beverages, alcohol intake, and smoking between participants of both the groups. Among hydration-related habits, it was observed that there was not much difference in the usage of throat lozenges between participants of both the groups. However, it was noted that the participants of group 1 had more water intake and much more frequent water intake than the participants of group 2. The use of vapor or steam inhalation was also more frequent among the participants of group 1 than in group 2.{Table 1}
Among the voice use-related habits, it was noted that the participants of group 2 reported frequent coughing, speaking at uncomfortable volumes throughout the day, and frequently engaged in screaming or yelling, or cheering. However, not many differences were observed in the duration of voice usage during the day, speaking in the presence of background noise, frequency of whispering during the day, participation of mimicry or singing, and indulgence in throat clearing during a day between the participants of both the groups.
The mean, median, and standard deviation values of the vocal behavior among the participants of group 1 and group 2 are displayed in [Table 2]. [Table 2] also shows the results of the Mann–Whitney U-test carried out to find out the significant differences in each vocal habit between the participants of both the groups. The Mann–Whitney U-test results showed that among the diet-related vocal habits, there were significant differences in the intake of caffeinated beverages, the time interval between meal and sleep, and the intake of oily and spicy food between the participants of both the groups. The results showed that group 2 reported a significantly higher intake of caffeinated beverages and oily and spicy food and had less time interval between meal intake and sleep than group 1. Across the hydration-related vocal habits, the results showed significant differences in water intake and the frequency of water intake between the participants of both the groups. There were no significant differences in the usage of throat lozenges and steam inhalation between the participants of both the groups. Thus, the results revealed that group 2 reported a significantly lower intake of water and less frequent water intake than the participants of group 1. The results also showed significant differences among the voice use-related habits across all the vocal habits between the participants of both the groups except for the hours of voice use per day and hours of speaking in background noise. Therefore, it was inferred from the results that the participants of group 2 reported a significantly higher frequency of throat clearing, coughing, raising in volume, whispering, mimicry or singing, and screaming.{Table 2}
Discriminant analysis was carried out to determine the set of vocal behaviors that discriminated between the participants of group 1 and group 2 and the results of the discriminant analysis have been presented in [Table 3]. All the vocal behaviors, that is, diet-related, hydration-related, and voice use-related behaviors, were considered predictor variables. The analysis of the structure matrix revealed only six significant predictors out of 18 predictor variables. The significant predictors of vocal behaviors were intake of oil and spicy food, rise in volume, frequency of voice use, screaming, throat clearing, and whispering. The cross-validated classification showed that 96.7% of samples were classified accurately by these six predictors between the participants of group 1 and group 2.{Table 3}
[Table 4] presents the descriptive and inferential statistics carried out on DSI and VRQOL scores between the participants of group 1 and group 2. The results of the descriptive statistics showed that the mean DSI value was higher for the participants of group 1 compared to that of group 2. The participants of group 1 had a positive mean DSI value, whereas the participants of group 2 showed a negative mean DSI value. The participants of group 1 had a lower standard deviation value than the participants of group 2, indicating that the DSI values in group 2 had higher variations. The Mann–Whitney U-test results revealed a significant difference in DSI values between the participants of both the groups. Thus, it was inferred that the participants of group 2 had significantly lower and negative DSI values compared to the participants of group 1. The participants of group 1 had positive DSI values that were significantly higher than those of group 2.{Table 4}
Regarding the VRQOL values, it was noted that mean VRQOL values for the participants of group 1 showed lower mean VRQOL values than the participants of group 2. The standard deviation values were also observed to be higher for the participants of group 2 compared to the participants of group 1. The Mann–Whitney U-test indicated a significant difference in VRQOL scores between the participants of group 1 and group 2. Therefore, the results implied that the VRQOL scores were significantly higher in the participants of group 2 compared to the participants of group 1.
Spearman's rank correlation coefficient was carried out to document the correlation between various vocal behaviors, DSI scores, and VRQOL scores. As it can be seen from [Table 5], among the vocal health behaviors, intake of oily and spicy food, water intake, rise in volume, cough, and screaming showed a low positive correlation with the DSI scores at an alpha value of 0.01. Other vocal health behaviors, including time intervals between the meal and sleep, throat clearing, mimicry/singing, and speaking with background noise, were noted to have little positive correlation with DSI scores. With respect to the correlation between the vocal health behaviors and VRQOL scores, it was evident that mimicry/singing, rise in speaking volume, and cough showed a low positive correlation with VRQOL scores at an alpha value of 0.01. Furthermore, little positive correlations were found between VRQOL scores and the intake of caffeine beverages, the time interval between meal and sleep, oily and spicy food, water intake, steam inhalation, throat clearing, whispering, screaming, and speaking in the background noise.{Table 5}
Further, to investigate the correlation between VRQOL and DSI scores, Spearman's rank correlation coefficient was carried out between DSI and VRQOL scores. DSI scores were correlated with the VRQOL total scores, scores of VRQOL social-emotional domain, and scores of VRQOL physical functional domain. The results of Spearman's correlation showed a significantly high positive correlation[32] between VRQOL total scores and DSI values (ρ = 0.74, /P/< 0.01). Significant high positive correlations were also noted between the social-emotional domain of VRQOL and DSI values (ρ = 0.72, /P/< 0.01), and between the physical-functional domain of VRQOL and DSI scores (ρ = 0.70, /P/< 0.01). Thus, it was inferred from the results of Spearman's rank correlation that there was a high positive correlation between VRQOL and DSI scores.
Discussion
The present study aimed to document the vocal habits and the relationship between vocal habits, DSI, and VRQOL in teachers with and without self-reported symptoms of dysphonia. The first objective of the study was to investigate the voice-related habits in primary school teachers with and without self-reported vocal symptoms, and the results revealed that among the vocal health-related habits, the intake of caffeinated beverages and spicy and oily food was most frequent in teachers with self-reported vocal symptoms and the time interval between intake of meals and sleep was observed to be shorter among the teachers with self-reported symptoms. Even though caffeine is considered to dehydrate the vocal folds and reduce the lubrication effects, some recent studies do not support notion empirically.[33] Therefore, the results of the present study have to be interpreted with caution, and the results do not imply that the caffeine intake can directly lead to symptoms of dysphonia. Teachers with self-reported symptoms of dysphonia also reported frequent coughing, speaking at uncomfortable volumes throughout the day, and frequent screaming, yelling, or cheering. Teachers without any self-reported vocal symptoms had more water intake and frequent use of vapor or steam inhalation. The systemic hydration through adequate water intake[34] or the surface hydration through inhalation of steam[35] can help in maintaining the viscoelastic properties of the vocal fold and quality of voice. Therefore, more water intake and frequent use of vapor or steam inhalation might have played a pivotal role in avoiding the presence of vocal symptoms of dysphonia among the teachers without self reported symptoms of dysphonia.
The present study results were in line with the earlier studies. Earlier study findings revealed that a few significant factors such as long hours of voice usage, speaking too loudly, continuous strain on voice, frequent and excessive throat clearing, usually speaking with a high pitch that may lead to voice problem among teachers.[36],[37] Along with this, lifestyle and diet-related habits, such as improper diet, smoking, and excessive alcohol intake, can cause dehydration problems and may also lead to voice disorders.[5] Therefore, the present study results support the findings of these earlier studies.
The second objective was to investigate the DSI and VRQOL scores among primary school teachers with and without self-reported symptoms of dysphonia. The results revealed that the DSI values were significantly higher in teachers without self-reported vocal symptoms. Teachers without self-reported symptoms had a positive DSI value, whereas those with self-reported symptoms of dysphonia showed a negative DSI value. Similar results were reported by an earlier study investigating DSI scores in elementary school female teachers with and without voice complaints. The results revealed that teachers without voice complaints have significantly higher DSI scores than those with voice complaints, and thus, the study concluded that there was a link between DSI scores and voice complaints.[24] Another study also investigated the DSI scores in teachers with permanent or frequent voice complaints and teachers without voice complaints. The result revealed that DSI was severely affected in both the groups and the range of DSI in teachers was between −5 and +5, with a more negative value of DSI indicating poorer quality of voice.[38] The present study results also revealed a similar finding wherein the teachers without self-reported vocal symptoms had positive DSI values, and the teachers with self-reported symptoms had negative DSI values. It is important to note that the DSI values largely depend on the maximum phonation time. Teachers without vocal symptoms might be expected to have a larger maximum phonation time and thereby have positive DSI values, whereas the teachers with self-reported symptoms of dysphonia might be expected to have lower maximum phonation time values and negative DSI values. Therefore, it can be inferred from the results of the earlier studies and the present study that the negative DSI values might indicate dysphonia or the symptoms of voice disorder among teachers.
With regard to the VRQOL values, mean VRQOL values among teachers without self-reported vocal symptoms were significantly lower than the VRQOL values of teachers with self-reported symptoms of dysphonia. These results were in consonance with that of the past literature. Aghadoost et al.[24] investigated the relationship between voice complaints and the quality of life in Persian-speaking Iranian teachers and reported that teachers with voice complaints have a poor general quality of life as well as the VRQOL. A recent study that investigated the VHI-10 and the VRQOL among Chinese teachers with and without voice disorders revealed that teachers with voice disorders have a poorer VRQOL, with more impairment seen among female teachers compared to male teachers.[39] Therefore, it can be inferred from the results of the present and past studies that the VRQOL was better among the teachers without any vocal symptoms than the teachers who reported vocal symptoms. As dysphonia can negatively influence health care and self-perceived productivity and cause voice-related absenteeism at work,[40] the teachers with self-reported vocal symptoms might be expected to have a poorer VRQOL compared to the teachers without any vocal symptoms.
The final objective of the present study was to document the relationship between vocal habits, DSI scores, and VRQOL. The results showed that vocal behaviors such as oily and spicy food, water intake, rise in volume, coughing, and screaming showed a significant positive correlation with the DSI scores. The results also showed that the vocal habits, namely, mimicry/singing, rise in speaking volume, coughing, the intake of caffeine beverages, the time interval between meal and sleep, intake of oily and spicy food, water intake, steam inhalation, throat clearing, whispering, screaming, and speaking in the background noise, showed a significant positive correlation with VRQOL. The present study results revealed a significant positive correlation between VRQOL total scores and DSI values, between the social-emotional domain of VRQOL and DSI values, and between the physical-functional domain of VRQOL and DSI scores. These results were in line with the results reported by earlier studies. A recent study attempted to determine the relationship between the DSI and VRQOL among elementary school teachers with voice complaints. The study result revealed positive correlations between the overall DSI and VRQOL scores obtained for the teachers' group with voice complaints, and the study also revealed that low DSI scores indicated a poor laryngeal function associated with lower VRQOL.[4] Another past study reported that there was a high correlation obtained between DSI and VHI scores.[13] Therefore, the present study results support the findings of all the earlier studies and conclude that the significant positive correlation between some of the vocal symptoms, DSI scores, and VRQOL could indicate that the presence of vocal behaviors that can have a negative impact on the voice can lead to the increase in the scores of both DSI and VRQOL. On the contrary, the presence of vocal behaviors that can positively impact the voice can lead to increased DSI scores. Higher DSI scores can indicate the absence of vocal symptoms or dysphonia and, hence, a better VRQOL.[41]
The present study had a few limitations. Gender-linked differences among the vocal habits, DSI scores, and VRQOL scores were not analyzed in the present study as major portions of the primary school teachers were females. Some information on whether teachers were involved in any other previous voice training programs or the vocal health information that might have influenced the vocal habits among teachers was not documented in the present study. The study also failed to document information on the working conditions, acoustical conditions of the classroom, and size of the student groups from the teachers. However, as only a handful of studies have focused on investigating Indian primary school teachers, the present study was a preliminary attempt to determine the relationship between vocal habits, DSI measurement, and VRQOL measurement in Indian primary schools.
Conclusion
The present study revealed that teachers with self-reported symptoms of dysphonia had more frequent habits such as consumption of beverages, intake of spicy and oily food, less time interval between intake of meals and sleep, coughing, speaking at uncomfortable volumes, and frequent screaming or yelling or cheering. Further, the results also revealed that teachers without self-reported symptoms had significantly positive DSI values and higher VRQOL values, whereas the teachers with self-reported symptoms of dysphonia showed negative DSI values and lower VRQOL. There was a significant positive correlation between VRQOL and the DSI values. Future studies can be conducted to find out how teachers with different years of experience differ in terms of vocal habits, vocal symptoms, DSI, and VRQOL. Studies can be also carried out to discern the impact of the classroom's size, population, background noise, and amplification equipment on teachers.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References
| 1 | Titze IR, Lemke J, Montequin D. Populations in the U.S. workforce who rely on voice as a primary tool of trade: A preliminary report. J Voice 1997;11:254-9. |
| 2 | Narasimhan SV, Gowda B. Multiparametric analysis of voice following prolonged voice use and voice rest in teachers: Evidence from discriminant analysis. Eur Arch Otorhinolaryngol 2022;279:1397-404. |
| 3 | Aishwarya SY, Narasimhan SV. The effect of a prolonged and demanding vocal activity (Divya Prabhandam recitation) on subjective and objective measures of voice among Indian Hindu priests. Speech Lang Hear 2022;25:498-506. |
| 4 | Mansouri Y, Naderifar E, Hajiyakhchali A, Moradi N. The relationship between dysphonia severity index and voice-related quality of life in the elementary school teachers with voice complaint. J Voice 2021. doi: 10.1016/j.jvoice.2021.02.017. |
| 5 | Sathyanarayan M, Boominathan P, Nallamuthu A. Vocal health practices among school teachers: A study from Chennai, India. J Voice 2019;33:812.e1-7. |
| 6 | Joshi AA, Mukundan P, Dave VJ, Bradoo RA, Dhorje NR. Prevalence of voice disorders in Indian female secondary school teacher population – A cross sectional study. Indian J Otolaryngol Head Neck Surg 2022;74:2324-30. |
| 7 | Aronson AE, Bless DM. Clinical Voice Disorders. 4th ed. New York: Thieme Medical Publishers; 2009. |
| 8 | Anniko M, Sprekelson MB, Bonkowsky V, Bradley P, Iurato S. Otorhinolaryngology, Head & Neck Surgery. 1st ed. New York: Springer Verlag GmbH; 2010. |
| 9 | van den Berg J. Myoelastic-aerodynamic theory of voice production. J Speech Hear Res 1958;1:227-44. |
| 10 | Hirano M. Morphological structure of the vocal cord as a vibrator and its variations. Folia Phoniatr (Basel) 1974;26:89-94. |
| 11 | Narasimhan SV, Vishal K. Spectral measures of hoarseness in persons with hyperfunctional voice disorder. J Voice 2017;31:57-61. |
| 12 | Narasimhan SV, Rashmi R. Multiparameter voice assessment in dysphonics: Correlation between objective and perceptual parameters. J Voice 2022;36:335-43. |
| 13 | Wuyts FL, De Bodt MS, Molenberghs G, Remacle M, Heylen L, Millet B, et al. The dysphonia severity index: An objective measure of vocal quality based on a multiparameter approach. J Speech Lang Hear Res 2000;43:796-809. |
| 14 | Soumya M, Narasimhan SV. Correlation between subjective and objective parameters of voice in elderly male speakers. J Voice 2020;36:823-31. |
| 15 | Wuyts FL, De Bodt M, Bruckers L, Molenberghs G. Research work of the Belgian Study Group on Voice Disorders 1996. Results. Acta Otorhinolaryngol Belg 1996;50:331-41. |
| 16 | Sobol M, Sielska-Badurek EM. The Dysphonia Severity Index (DSI)-normative values. Systematic review and meta-analysis. J Voice 2022;36:143.e9-13. |
| 17 | Yu L, Lu D, Yang H, Zou J, Wang H, Zheng M, et al. A comparative and correlative study of the Voice-Related Quality of Life (V-RQOL) and the Voice Activity and Participation Profile (VAPP) for voice-related quality of life among teachers with and without voice disorders. Medicine (Baltimore) 2019;98:e14491. |
| 18 | Nusseck M, Spahn C, Echternach M, Immerz A, Richter B. Vocal health, voice self-concept and quality of life in German school teachers. J Voice 2020;34:488.e29-39. |
| 19 | Devadas U, Kumar PC, Maruthy S. Prevalence of and risk factors for self-reported voice problems among Carnatic singers. J Voice 2020;34:303.e1-15. |
| 20 | Hogikyan ND, Sethuraman G. Validation of an instrument to measure voice-related quality of life (V-RQOL). J Voice 1999;13:557-69. |
| 21 | Ma EP, Yiu EM. Voice activity and participation profile: Assessing the impact of voice disorders on daily activities. J Speech Lang Hear Res 2001;44:511-24. |
| 22 | Jacobson BH, Johnson A, Grywalski C, Silbergleit A, Jacobson G, Benninger MS, et al. The Voice Handicap Index (VHI): Development and validation. Am J Speech Lang Pathol 1997;6:66-9. |
| 23 | Murry T, Medrado R, Hogikyan ND, Aviv JE. The relationship between ratings of voice quality and quality of life measures. J Voice 2004;18:183-92. |
| 24 | Aghadoost O, Amiri-Shavaki Y, Moradi N, Jalai S. A comparison of Dysphonia Severity Index in female teachers with and without voice complaints in elementary schools of Tehran, Iran. Nurs Midwifery Stud 2013;1:133-8. |
| 25 | Hummel C, Scharf M, Schuetzenberger A, Graessel E, Rosanowski F. Objective voice parameters and self-perceived handicap in dysphonia. Folia Phoniatr Logop 2010;62:303-7. |
| 26 | Smith E, Gray SD, Dove H, Kirchner L, Heras H. Frequency and effects of teachers' voice problems. J Voice 1997;11:81-7. |
| 27 | Vilkman E. Voice problems at work: A challenge for occupational safety and health arrangement. Folia Phoniatrica et Logopaedica 2000;52:120-5. https://doi.org/10.1159/000021519. |
| 28 | Mahajan V, Gore GB. Voice Related Quality of Life (V-RQOL): Impact of vocal hygiene programme in secondary school teachers. Int J Health Sci Res 2016;6:307. |
| 29 | American National Standards Institute S3.21:2004. Methods for manual pure-tone threshold audiometry. Bioacoustics 2009. |
| 30 | Boersma P, Weenink D. Praat: doing phonetics by computer [Computer program]. 2019. (Version 6.0.56 retrieved from http://www.praat.org/). |
| 31 | IBM SPSS Statistics for Windows Version 24.0. IBM Corp. Released (Version 24.0). Armonk, NY: IBM Corp; 2016. |
| 32 | Hinkle DE, Wiersma W, Jurs SG. Applied Statistics for the Behavioral Sciences. 5th ed. London, Boston, Mass: Houghton Mifflin; 2003. |
| 33 | Georgalas VL, Kalantzi N, Harpur I, Kenny C. The effects of caffeine on voice: A systematic review. J Voice 2021. Available from: https://www.sciencedirect.com/science/article/pii/S0892199721000849. [Last accessed on 2023 Jan 04]. |
| 34 | Alves M, Kruger E, Pillay B, van Lierde K, van der Linde J. The effect of hydration on voice quality in adults: A systematic review. J Voice 2019;33:125.e13-28. |
| 35 | Leydon C, Sivasankar M, Falciglia DL, Atkins C, Fisher KV. Vocal fold surface hydration: A review. J Voice 2009;23:658-65. |
| 36 | Devadas U, Bellur R, Maruthy S. Prevalence and risk factors of voice problems among primary school teachers in India. J Voice 2017;31:117.e1-10. |
| 37 | Remacle A, Morsomme D, Finck C. Comparison of vocal loading parameters in kindergarten and elementary school teachers. J Speech Lang Hear Res 2014;57:406-15. |
| 38 | Majeed NA, Haneefa H. An evaluation of dysphonia among teachers. Int J Sci Study 2017;5:101-9. |
| 39 | Lu D, Wen B, Yang H, Chen F, Liu J, Xu Y, et al. A comparative study of the VHI-10 and the V-RQOL for quality of life among Chinese teachers with and without voice disorders. J Voice 2017;31:509.e1-6. |
| 40 | Cantor Cutiva LC, Burdorf A. Factors associated with voice-related quality of life among teachers with voice complaints. J Commun Disord 2014;52:134-42. |
| 41 | Schneider S, Plank C, Eysholdt U, Schützenberger A, Rosanowski F. Voice function and voice-related quality of life in the elderly. Gerontology 2011;57:109-14. |
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