Voice is an instrumental component of communication and, according to Sivasankar (2002), more than one-third of the current global labor works in fields where voice is crucial for the attainment of positive professional outcomes. Healthy voices are used as instruments for the wellbeing of many professionals in the social, mental and economic fields. One of the aforementioned professions that rely on voice is teaching and, as highlighted by Goodyear and Dudley (2015), teachers make the greatest impact in the society due to their influence in knowledge acquisition, transfer, and retention. For teachers, voice plays a significant role in the delivery of messages through any verbal communication while conducting their professional duties. However, in some instances, the efficiency of speech of teachers can be hampered due to voice fatigue.

Voice fatigue occurs when the voice organs are used for a long time, but ends after some period of rest (Nanjundeswaran, Van Swearingen, & Abbott, 2017). The main challenge faced by speech therapists, voice coaches and other experts in this era is the lack of a clear definition of voice fatigue. The term voice fatigue is primarily defined based on the decrements in the performance of the output of force through the larynx following activity of a certain magnitude. The fatigue in the voice of an individual is an early indicator of underlying problems that include but are not limited to larynx infections and overall voice disorders. The increased prevalence of voice disorders among professionals in different segments has prompted speech therapists, and other professionals that deal with the oral cavity, to define scales and indices that they can employ in the evaluation of underlying problems and the examples include Voice Handicap Index (VHI) and Voice Fatigue Index (VFI). The two scales are the instruments primarily being used to assess clinical issues related to the vocal cords.

The effectiveness of message delivery by verbal means depends on voice clarity. Under normal circumstances, a speaker is expected to address the audience without any voice interruptions. However, according to Rajasudhakar and Savithri (2010), there is a significant prevalence of voice problems among voice professionals in various industries within the global arena. Voice fatigue has therefore caused inefficiencies in communication, in a number of sectors including the education segment. A survey by Sivasankar (2002) established that 50-80% of educators experience vocal problems, which negatively affect their performance. Additionally, the prevalence of voice fatigue among high school teachers in India was estimated at 49%, which is quite high and problematic. Therefore, the central problem that this study assesses using the VFI scale is the increased prevalence of voice problems among Indian teachers.

The documented literature indicates that several risk factors are responsible for voice fatigue. For example, Pizolato, Mialhe, Laura, Beltrati, and Pereira (2015) explained that voice fatigue could be caused by old age, alcohol consumption, allergies, and reflux disease of the gastroesophageal. It could also be caused by infections of the respiratory tract, colds, neurosurgical disorders, and psychological stress, neck trauma due to accidents and surgery, as well as smoking. Other factors that may lead to voice fatigue are throat cancer, dehydration of the voice cord, thyroid problems, and the overuse or misuse of the voice. Przysiezny and Sanson (2016) explained that the occupational risk factors for voice fatigue could be grouped into two categories, which are organizational and environmental factors. The organizational factors include the processes of work such as overload, absence of breaks, autonomy, stress at the place of work, and dissatisfaction with the workplace due to poor remunerations. However, environmental risk factors for voice fatigue include physical hazards such as a sudden increase in sound pressure, temperature changes, lack of proper illumination, and poor ventilation.

According to Pizolato et al. (2015), teachers who were smokers and those who had experienced infections of the larynx reported cases of voice fatigue and the analysis further showed that 66.66% of the teachers suffered voice fatigue due to shouting while 52.96% experienced voice fatigue due to previous experience of cold. Alvear and Arquero (2015) agreed with Pizolato et al. (2015) but added that males had a more likelihood of developing voice fatigue than the females. However, Alva, Machado, Bhojwani, and Sreedharan (2018) contradicted Alvear and Arquero (2015) by showing that females had a higher frequency of experiencing voice fatigue than men, with percentage frequencies of 96.3% and 3.7%, respectively. The number of years of service in the teaching profession had influence with a probability of 0.117 as indicated by Alva et al. (2018).

Banks, Bottalico, and Hunter (2017) studied the impact of classroom capacity on the possibility of occurrence of voice fatigue and the results of the analysis using the Poisson-log linear Generalized Linear Model and indicated that 60% of the teachers were experiencing vocal fatigue at the time of the study. The results further indicated that the probability of occurrence of voice fatigue increased with the expansion of class size, with an average score of 4.5 and a standard error of 0.51 as opposed to 0.31 indicated by Pizolato et al. (2015). Assuncao, Bassi, Medeiros, Rodrigues, and Gama (2014) used the Job Stress Scale Instrument to investigate risk factors of voice fatigue in teachers and the results indicated that health conditions of the teachers such as problems with the respiratory tract, gastritis, disorders in sleeping, problems with mental health, lack of regular medical check-up, and absenteeism are also significant contributing factors.

Bolbol, Zalat, Hammam, and Elnakeb (2016) applied the VHI scale to the life of teachers and the results showed that a work duration of more than 15 years had an index of 2.46 at a 95% confidence limit. A number of lessons, loudness of voice, age, gender, and marital status had indices of 3.96, 2.55, 1.05, 1.56, and 3.63, respectively. The above results coincide with the works of Majeed and Haneefa (2017) who established that work experience, duration of work, number of students, and previous health conditions had a significant effect in causing voice fatigue.

Research conducted by Sivasankar (2002) on voice fatigue among Indian teachers established a significant difference between the prevalence of voice fatigue among the Indian teachers, before and after they get into the teaching profession. The frequency of occurrence of voice fatigue increased from 3 times per year before being involved in full-time teaching, to 2 times a week after full-time engagement in the teaching activities. The above result is supported by a similar study conducted by Devadas, Bellur, and Maruthy (2017) on 1082 teachers in India that indicated a 17.4% rate of prevalence.

In another study, Hamid, Eldessouky, Iskender, and Hassan (2015) considered a sample of 250 teachers in India and used the Auditory Perceptual Assessment (APA) method and the results showed that female teachers had a higher voice fatigue prevalence than the male ones, with a standard deviation of 7.68 for age and 7.102 for the years in the teaching profession. Weekly teaching hours had an average of 20.14 and a standard deviation of 5.64. The frequency of voice fatigue among the teachers was 23.2, which represented a 58% level of prevalence, with a p-value of 0.398 and Pearson’s coefficient of 0.71. The research works provide a comprehensive overview of the state of dysphonia among the Indian teachers but do not show any difference in the results of both VHF and VIF that are used for the analysis.

Morawska and Bogusz (2017) conducted a research to establish the prevalence of voice fatigue among Indian teachers and established that the rate of prevalence was 20.51%, with a standard deviation of 44.26 from the general population. The survey also showed that teachers in India had a 15% higher chance of reporting voice fatigue than respondents from other occupations, who exhibited a 6% probability of suffering from voice fatigue. The research further indicated that female teachers had 87% chances of reporting voice fatigue, compared to 17% for the males. A study by Ramprasad, Das, and Maruthi (2017) considered a sample size of 3258 teachers randomly selected from 115 schools in India and their findings support the above results established by Morawska and Bogusz (2017). In particular, the research established that the prevalence of vocal fatigue among the Indian teachers was 27%, with an average of 27.5 hours in class. The study further indicated that the number of hours spent in class was the most significant cause of voice fatigue (36%), while midday classes contributed to the highest number of incidences of voice fatigue when the time of activities is considered.

Conversely, a study by Stachlert (2018) indicated different results in research, where the prevalence of voice fatigue among Indian teachers in nursery schools is 45.2%. However, the causes of the significant difference between prevalence rates of vocal fatigue among teachers in nursery and upper primary education levels are not explained. Rafee, Zambon, Behlau, and Badaro (2018) used the VFI scale to establish the prevalence of vocal fatigue among 60 Indian teachers and established a prevalence rate of 22%, which was considerably low as compared to the results of other above as presented above. The research further showed that teachers who sought for treatment of voice irregularities after the occurrence of voice fatigue had higher chances of experiencing the condition.

The documented literature identified VFI and VHI scales as the two main instruments that are being used widely by researchers to measure and assess voice fatigue. For instance, a study by Nanjundeswaran, Jacobson, Schmidt, and Abbott (2015) indicated the VHI scale become more effective since the voice validation index is done in 3 stages, as opposed to the 2 stages adopted by Hunter and Banks (2017). As explained by Hunter and Banks (2017), the two scales rely on the index generation that focuses on the development of questions that target the main symptoms of voice fatigue. However, the viability of the questions included in the two scales is limited by the fact that voice fatigue had a general definition, and could incorporate other infections that are not related to the voice. Notably, the literature has not documented research works that indicate a clear difference between the sensitivity and validity of VFI and VHI.

The development of VFI by Nanjundeswaran et al. (2017) considered gender and age of the respondents, and excluded those who had previously been treated against illnesses that were identical to, or were related to the symptoms of voice fatigue. However, the research does not indicate how patients with primary voice fatigue and those that displayed symptoms of voice fatigue but actually had other illnesses are identified and isolated from the study. The analysis grouped the indicator factors into 3 groups, which were voice tiredness (factor 1), physical discomfort (factor 2), and rest for symptom enhancement (factor 3). Athira and Devadas (2019) evaluated the reliability of the VHI scale through the test-retest framework and yielded a Pearson coefficient of 0.94, which was significant. The same procedure was used by Assuncao et al. (2014) to assess the reliability of VFI and established the Pearson coefficient of 0.91, which was also significant. In essence, the above studies indicate that both VFI and VHI scales are reliable for measuring the extent of voice fatigue.

On the other hand, a research study conducted by Rafee, Zambon, Badaro, and Behlau (2019) on the validity of the VFI scale using Cronbach’s alpha and the t-test found that it is internally consistent. Conversely, an analysis of VFI scale by Athira and Devadas (2019) considered 3 factors, which are voice tiredness, limiting the use of voice, and symptoms of physical discomfort, which yielded standard deviations of 0.922, 0.923, and 0.925 respectively, with probability values less than or equal to 0.001 with 80% sensitivity and 71.4% specificity. However, a study by Broek, Heinjen, Hendriksma, Langeveld, and Benthem (2019) indicated that the specificity for the same factors is 83.2%. Therefore, VFI was considered appropriate in the analysis of voice fatigue due to the significant levels of specificity and sensitivity for all three factors.

On the other hand, Rafee et al. (2019) performed an analysis of logistic regression to establish the extent of sensitivity of the VFI scale. The regression was performed in the forward stepwise manner and yielded a chi-square value of 35.05 with a probability of p<0.000. The sensitivity value was 0.91, indicating that VFI was a reliable and efficient tool for the evaluation of voice fatigue within a given population. VFI indicated 89% chances of predicting accurate results within the group that had not experienced voice fatigue, and a 94% chance of accurately predicting results within the group that had experienced voice fatigue in the past. The research works do not indicate specificity and sensitivity values yielded when VHI and VFI are used for the analysis of the same sets of data. Based on the above evidence, the current study will use the VFI scale to measure the extent of voice fatigue among Indian teachers due to its reliability.