A Contributory Study of the Factors in British and Iranian English Instructors’ Teacher Immunity

Introduction

A close scrutiny of the relevant studies (e.g. Kamrani et al., 2023; Kayed & Kazemian Moghadam, 2021; Li et al., 2019; Martin & Mulvihill, 2019; Mercer & Gregersen, 2020; Namaziandost et al., 2022, 2022; Salehizadeh et al., 2020; Zohrabi & Akbarzadeh, 2023; Zohrabi & Bimesl, 2022) shows that language teacher factors have attracted attention in the field of language teaching in recent decades. Cirocki and Farrell (2019) defined these factors as affective and cognitive characteristics of language teachers that directly or indirectly affect their teaching effectiveness. As Lindvall et al. (2018) noted, these factors also include the numerous teacher-internal variables that mediate the effects of teachers’ pedagogical practices on learners’ language acquisition.

From the above definitions, it is clear that studies of teacher factors involve the examination of certain teacher internal variables (Mercer & Gregersen, 2020). These variables include teacher resilience (e.g., Farrokhi, et al., 2023; Richards et al., 2016; Shirazizadeh et al., 2019), teacher perfectionism (e.g., Stoeber, & Corr, 2015), professional development (e.g., Derakhshan et al., 2020), teacher self-efficacy (Xiyun et al., 2022), work engagement (e.g., Xie, 2021), burnout (e.g., Rashtchi, & Sanayi Mashhour, 2019), and work motivation (e.g., Amirian et al., 2023), among others. However, teacher immunity (TI) is a controversial factor among the above-mentioned teacher factors and has gained importance in the last decade (Cirocki & Farrell, 2017; Dobakhti, et al., 2022). Hiver (2015) introduced TI to the field of language teaching as an overarching construct that determines the mental health of language teachers. More specifically, he borrowed the metaphor of immunity from the field of medicine and drew a comparison between the biological immune system and the psychological protection system. As a result, he defined TI as a metaphorical and psychological protective shield that shelters teachers from the multitudinous contextual stressors in their workplace. Moreover, as he noted, personal and affective variables can influence TI.

In the field of language teaching, teachers’ age and income have been among the most examined personal factors (Klassen & Chiu, 2010). In addition to these personal factors, teachers’ Emotion Regulation (ER), Teacher Reflection (TR), Professional Identity (PI), and grit have been among their frequently investigated affective factors (Taxer & Gross, 2018). Hiver’s (2015) view on the role of teacher factors in TI shows that it is necessary to specify the factors in language instructors’ TI in second and foreign language contexts for determining the major sources of stress that reduce their pedagogical efficiency and complicate language teaching problems.

Review of the Related Literature

TI

Hiver (2017) delved more deeply into the structure of TI and endeavored to specify its subcomponents. To this end, he used factor analysis and identified seven important subcomponents of TI, including burnout, affectivity, attitude towards teaching, coping, teaching self-efficacy, resilience, and openness to change. As Hiver (2017) stated, burnout in English teachers refers to their psychological exhaustion due to contextual stressors that affect their optimal performance. In addition, affectivity encompasses the range of teachers' emotions in the process of language teaching. Attitude towards teaching indicates how teachers perceive the effectiveness of their pedagogical practices. In addition, coping encompasses teachers’ ability to utilize various affective strategies to alleviate their psychological tension. In addition, teaching self-efficacy determines teachers’ view of the benefits of their teaching practices. Besides, resilience specifies the instructors’ acclimatization to various situations. Finally, openness to change encompasses instructors’ tendency to modify their teaching principles based on instructional developments.

In addition to his work on the structure of TI, Hiver collaborated with his colleagues to itemize the types of this construct. Accordingly, Hiver and Dörnyei (2017) distinguished language teachers’ productive TI from their maladaptive TI based on their psychological composure. They explained that productive TI is comparable to an efficient immune system as it prompts teachers to utilize their inner resources, such as self-confidence, to cope with stressors and protects them from tension-inducing factors. On the other hand, maladaptive TI resembles an overactive immune system as it reacts to harmless factors such as innovations in language teaching, turning teachers into cynical practitioners and leading to their obstinacy and inflexibility. Hiver and Dörnyei (2017) noted that the underlying features of TI distinguish it from cognate constructs including adaptability, buoyancy, and engagement among others.

As Collie and Martin (2017) stated, language teachers’ adaptability encompasses their ability to take advantage of specific stress-management strategies in order to control their cogitation and emotions and to acclimatize themselves to the changes in teaching conditions. Hiver and Dörnyei (2017) noted that the definition of adaptability shows that it is comparable to the coping and resilience sub-components of TI and does not deal with the other
sub-components. Moreover, Parker and Martin (2009) pointed out that buoyancy refers to language teachers’ ability to deal with diverse challenges that stem from student-related, context/setting-oriented, or personal issues in their academic settings. Hiver and Dörnyei (2017) drew a comparison between the buoyancy and the affectivity sub-component of TI and stated that buoyancy does not account for the other aspects of TI. Lastly, Maslach (2011) noted that language teachers’ engagement refers to their instructional persistence that prompts them to allocate their energy to language instruction and to take advantage of the available resources in order to facilitate and expedite learners’ language acquisition in the context of the classroom. Hiver and Dörnyei (2017) noted that engagement is analogous to attitudes towards the teaching sub-component of TI and does not address the remaining sub-components. Considering these discussions, Hiver and Dörnyei (2017) concluded that TI constitutes a comprehensive factor that represents the totality of language teachers’ psychological health in their academic settings.

Teacher Factors

Kim and Roth (2011) stated that teachers’ age and income constitute two of their most significant personal factors. They defined teachers’ age as the biological age of their body. Moreover, they pointed out that, in general, teachers’ income is equated with their monthly wages along with their added bonuses.

In addition, Yuan and Zhang (2020) pointed out that ER, TR, PI, and grit are regarded to be influential affective language teacher factors. Gross (2014) defined teachers’ ER as their ability to exert conscious control over their various feelings and to capitalize on their positive emotions to manage their language instruction. Gross (2015) distinguished overt ER from covert ER based on their automaticity. According to him, overt ER refers to teachers’ explicit management of their emotions and is reflected in their intentional behavioral modification. On the other hand, covert ER encompasses teachers’ automatic and unconscious control of their aroused emotions. Based on this distinction, Gross (2015) argued that instructors with high covert ER are able to select teaching situations that are less threatening and can modify the relevant situations to deal effectively with their stress-inducing factors. Moreover, these teachers can exert control over their emotional experiences by managing the focus of their attention. They are also able to associate positive meanings with previous disturbing experiences by capitalizing on their positive feelings. Finally, they are able to stifle the negative emotions that interfere with their effective language instruction.

Gheith and Aljaberi (2018) stated that TR involves a metacognitive skill that enables teachers to gain a satisfactory understanding of various aspects of the target language and acquire professional expertise for teaching it. They defined TR as teachers’ problem-solving process in which they question their techniques to identify their pedagogical weaknesses and strengths and use creative solutions to improve their teaching effectiveness. Farrell (2016) also stated that TR empowers teachers to improve their teaching effectiveness by transferring the pedagogical strengths of their previous teaching experiences to similar teaching situations.
As he explained, language teachers with a high level of TR do not limit themselves to conventional teaching methods and are likely to use alternative teaching methods that can improve learners’ acquisition of the target language. Furthermore, these teachers see themselves as active learners who spend a noticeable amount of time in contemplation to ameliorate their teaching ability.

According to Sachs (2005), teachers’ PI is an affective factor that can affect their academic performance as it influences a number of factors internal to the teacher. He defined identity as an individual’s sense of being a member of a particular community, which is dynamically influenced by contextual factors and reshaped over time. Considering this definition, Xiang (2021) pointed out that teachers’ PI involves the perpetual process of personal growth, which enables them to develop pedagogical competence and helps them adapt to different teaching conditions in various academic environments. Yuan and Zhang (2020) have discussed the various aspects of PI development and concluded that it enables teachers to improve their teaching effectiveness and promote learners’ language acquisition.

Vaknin-Nusbaum and Tuckwiller (2023) found that language teachers’ grit is one of the most important predictors of their pedagogical success. They defined grit as teachers’ interest in their profession and their passion for improving learners’ language acquisition, which accelerates the achievement of their goals. According to Steinmayr et al. (2018), grit is a crucial factor in teachers’ pedagogical effectiveness. They stated that teachers who have high levels of grit maintain interest in their profession despite the great challenges of language teaching. Moreover, these teachers strive to improve their pedagogical performance in their academic environment without being negatively affected by stressful factors.

Purpose of the Study

TI is an unexplored area in teacher factor studies. More specifically, empirical studies on this construct have focused on certain issues and have completely ignored others. Some of them (e.g., Dobakhti, et al., 2023a; Haseli Songhori et al., 2018; Hiver & Dörnyei, 2017; Maghsoudi, 2021) have attempted to specify the dominant TI type of language teachers. Some others (e.g. Aliakbari & Fadaeian, 2023) have investigated the extent to which TI influences teachers’ perceptions of teaching practices such as translanguaging. In addition, some studies (e.g., Dobakhti, et al., 2023b; Khazaeenezhad &, Davoudinasab, 2022) have examined the interplay between personality and TI, and a few (e.g., Khalili, et. al., 2024; Pourbahram & Sadeghi, 2020; Rahmati et al., 2019) have compared teachers’ TI in different language teaching situations.

However, the above studies have not examined the role of personal factors (i.e., age & income) along with affective factors such as ER, TR, PI, and grit in teachers’ TI. Furthermore, these studies have mainly focused on one context and have not looked at other contexts. Finally, the relevant studies have not investigated the likely differences between language teachers’ TI in different contexts. The present study aimed to address these issues in England and Iran. Accordingly, it endeavored to answer the following three research questions:

1. What are the factors in British EFL teachers’ TI?
2. What are the factors in Iranian EFL teachers’ TI?
3. What are the differences between British and Iranian EFL teachers’ TI?

Methods

Participants

With regard to the main objectives, the researchers used convenience sampling for selecting 283 (i.e. 124 male and 159 female) British EFL teachers at various private language institutes in nine cities in England, including London, Birmingham, Nottingham, Bristol, Leicester, Southampton, Plymouth, Hull, and Derby. These teachers were aged between 26 and 58 and had a bachelor's, master's, or doctorate degree in an English-language subject. In addition, the researchers used the same sampling method to select 295 (i.e. 141 male and 154 female) EFL teachers in twelve cities in Iran, including Urmia, Tabriz, Ardabil, Zanjan, Karaj, Yasuj, Kermanshah, Rasht, Shiraz, Kerman, Ahvaz, and Yazd. These teachers were between 24 and 61 years old and were similar to the British teachers in terms of their university degrees. They also spoke Azeri, Kurdish, Farsi, or Arabic as their mother tongue. All participants gave written informed consent to the researchers before data collection began.

Instruments

The researchers used the following instruments in this study:

TI Questionnaire

Hiver’s (2017) TI questionnaire was used to collect data on British and Iranian English teachers’ TI. This instrument includes 39 items that were rated on a seven-point Likert scale. Hiver (2017) found that this questionnaire had satisfactory reliability and validity indices. Nevertheless, Cronbach’s alpha (CA) was used to investigate the reliability of this instrument in England and Iran in a pilot study with 29 British and 28 Iranian English teachers. The results show that the reliability indices in England and Iran are 0.84 and 0.81 respectively. Therefore, the researchers used this instrument. The cut-off point of Hiver’s (2017) TI questionnaire was 156, and accordingly, TI scores that were below 156 were categorized as maladaptive TI, and TI scores above 156 were categorized as productive TI.

Demographic Information Questionnaire

A researcher-developed demographic questionnaire was employed for determining British and Iranian teachers’ gender, age, experience (in years), and income (in US dollars).

ER Questionnaire

The ER questionnaire by Heydarnejad et al. (2021) was adopted to investigate the ER of British and Iranian English teachers. It comprises 27 items on a five-point Likert scale. The results of the CA analysis show that the reliability indices of this instrument in England and Iran are 0.87 and 0.82, respectively. Therefore, it could be used to collect data on participants’ ER.

TR Questionnaire

The TR questionnaire by Akbari et al. (2010) was utilized to examine the TR of the British and Iranian participants. This instrument comprises 29 items on a five-point Likert scale. The results of the CA analysis show that the reliability indices in England and Iran are 0.81 and 0.88, respectively. Therefore, it was used in the present study.

PI Questionnaire

Kao and Lin’s (2015) PI questionnaire was used to collect data on British and Iranian teachers’ PI. This self-assessment questionnaire includes 22 items on a five-point Likert scale. Based on the results of the CA analysis, the reliability indices of this instrument were 0.87 and 0.82 in the contexts of England and Iran respectively. Therefore, the researchers used this questionnaire in the study.

Grit Questionnaire

In light of the main purpose, the researchers used Duckworth and Quinn’s (2009) grit questionnaire to determine British and Iranian participants’ grit. This instrument involves 8 five-point Likert-scale items. According to the results of the CA analysis, the reliability indices of this questionnaire were 0.89 and 0.85 in the contexts of England and Iran, respectively. Therefore, it was employed in this study.

Procedure

The researchers examined 54 prominent language institutes in nine cities in England, including London, Birmingham, Nottingham, Bristol, Leicester, Southampton, Plymouth, Hull and Derby. The websites of these language institutes were then checked and the email addresses of the teachers were obtained. The preliminary search provided the researchers with information on 567 teachers, including 239 male and 328 female teachers. They were contacted to be informed about the aims and process of the study and invited to participate in the study within a two-month period. However, 181 teachers (97 men and 84 women) did not respond to the researchers’ emails and 103 teachers (76 men and 27 women) did not participate in the study for various reasons, such as their busy schedules and others. Finally, 283 UK teachers (124 males and 159 females) agreed to take part in the study. The six questionnaires were distributed to these participants using Google Forms, which the participants completed and returned in a one-month period of time.

In addition, 66 prestigious language institutes were identified in twelve cities in Iran, including Urmia, Tabriz, Ardabil, Zanjan, Karaj, Yasuj, Kermanshah, Rasht, Shiraz, Kerman, Ahvaz and Yazd. The administrative departments of the concerned institutes were contacted and the contact details of 622 (291 male and 331 female) EFL teachers were obtained.
The researchers first sent an email to these teachers to inform them about the objectives of the study and ask them to take part. If they had not received a response after two weeks, another email was sent. However, 259 instructors (166 men and 93 women) did not respond to the emails. In addition, 68 teachers (49 males and 19 females) who had responded were not interested in participating in the study. Therefore, 295 Iranian teachers (141 males and 154 females) participated in the study. The researchers distributed all of the above questionnaires to these teachers using Google Forms. These participants completed and returned the questionnaires in a two-month time period.

Design

This study was conducted using a predictive correlation design. According to Creswell (2009), researchers use this design to determine the factors that predict the variance of a criterion variable. Accordingly, in this study, the researchers examined the age, income, ER, TR, PI, and Grit of British and Iranian English teachers as predictors of the variance of their TI in their academic settings.

Data Analysis

Considering the main objectives of the study, the researchers used Binary Logistic Regression (BLR) and Chi-square test for independence to perform the data analysis. Pallant (2007) noted that BLR enables the researchers to specify the independent variables (i.e. factors) that predict the variance in a categorical variable. Accordingly, in this study, the researchers used BLR to examine the degree to which British and Iranian teachers’ age, income, ER, TR, PI, and grit (i.e. independent variables) predicted the variance in their productive and maladaptive TI (i.e. categorical dependent variable). Furthermore, Pallant (2007) pointed out that the Chi-square test for independence empowers the researchers to determine the significant differences between the frequencies of the categories of two categorical variables. Accordingly, the researchers used the Chi-square test for independence to specify the significant difference between the productive and maladaptive categories of British and Iranian English teachers’ TI.

Results

Question one investigated the main predictors of British teachers’ productive and maladaptive TI. Therefore, the researchers used BLR in the data analysis. Pallant (2007) pointed out that the main assumption of this test is the multicollinearity assumption that can be checked using the Tolerance values of the independent variables. Accordingly, first, the researchers tested the assumption of multicollinearity by examining the tolerance values. The results indicated that the tolerance values were greater than 0.1. Consequently, the multicollinearity assumption was not violated (Pallant, 2007). Based on these results, the researchers examined the tests of the model coefficients to determine the goodness of fit of the model in question. Table 1 shows the results:

Table 1. Omnibus Tests of Model Coefficients of British Teachers’ Productive and Maladaptive TI

Based on Table 1, the results were significant (p<0.05). Therefore, the researchers examined the goodness of fit. Table 2 shows these results:

Table 2. Hosmer and Lemeshow Test of British Teachers’ Productive and Maladaptive TI

According to Table 2, the goodness of fit result was not significant (p>0.05). As a result, a summary of the model was examined (Pallant, 2007). Table 3 shows these results:

Table 3. Model Summary of British Teachers’ Productive and Maladaptive TI

The values in Table 3 highlighted the fact that the model explained between 30.1 and 42.2 percent (i.e. R Square values multiplied by 100) of the variance in British teachers’ productive and maladaptive TI. Based on these results, contributions of predictor factors to these participants’ productive and maladaptive TI were examined. Table 4 provides the results:

Table 4. Factors in Equation on British Teachers’ Productive and Maladaptive TI

Examination of the Wald scores and associated probability values in Table 4 shows that UK teachers’ ER (13.695), TR (6.816), and PI (4.911) were the first, second, and third predictor variables, respectively, that made the strongest significant contribution to explaining their productive and maladaptive TI.

The second question aimed to identify the significant predictors of Iranian English teachers’ productive and maladaptive TI. Therefore, BLR was used in the data analysis. First, the researchers tested the assumption of multicollinearity by examining the collinearity diagnosis. Based on the results, none of the values was less than 0.1. As a result, the multi-collinearity assumption was not violated and tests of model coefficients (goodness of fit tests) were examined. Table 5 shows these results:

Table 5. Omnibus Tests of Model Coefficients of Iranian Teachers’ Productive and Maladaptive TI

According to Table 5, the pertinent results were significant (p<0.05). Consequently, researchers examined goodness of fit results. Table 6 provides these results:

Table 6. Hosmer and Lemeshow Test of Iranian Teachers’ Productive and Maladaptive TI

As shown in Table 6, goodness of fit result was not significant (p>0.05). Therefore, a summary of the relevant model was examined. Table 7 shows the relevant results:

Table 7. Model Summary of Iranian Teachers’ Productive and Maladaptive TI

According to Table 7, the model explained between 66.3 and 89.5 percent of the variance in Iranian English instructors’ productive and maladaptive TI. Based on these results, contributions of predictor factors to these participants’ productive and maladaptive TI were examined. Table 8 provides these results:

Table 8. Variables in Equation on Iranian Teachers’ Productive and Maladaptive TI

Examination of the Wald scores and their respective probability values in Table 8 shows that income (11.498), age (7.241), and ER (5.726) of Iranian English teachers were the first, second, and third predictor variables, respectively, that made the strongest significant contribution in explaining their productive and maladaptive TI.

Finally, the third question aimed to determine the difference between British and Iranian English teachers’ productive and maladaptive TI. Considering this objective, the researchers used the chi-square test for independence in the data analysis. Table 9 shows the frequency and percentage of productive and maladaptive TI of British and Iranian English teachers:

Table 9. Frequency and Percentage of British and Iranian Teachers’ Productive and Maladaptive TI

Moreover, Table 10 shows the results of the Chi-square test:

Table 10. Chi-Square Test of British and Iranian Teachers’ Productive and Maladaptive TI

Pallant (2007) noted that in 2 by 2 Chi-square tables, the Continuity Correction value has to be checked instead of the Pearson Chi-Square value. The examination of this value in Table 10 showed that the result was significant (p<0.05). Therefore, British instructors’ productive and maladaptive TI significantly differed from that of Iranian instructors.

Discussion

The first question investigated the factors underlying the productive and maladaptive TI of UK teachers. The results showed that ER, TR, and PI were the first, second, and third main predictors of participants' TI respectively. In general, these results confirm the findings of a number of previous studies, including the studies by Talbot and Mercer (2018), Rashtchi and Sanayi Mashhour (2019), Rahimpour et al. (2020), Fathi et al. (2021), Deng et al. (2022), Li et al. (2022), Namaziandost et al. (2024), and Xiyun et al. (2022). These studies reported that teachers’ affective factors (e.g., ER, engagement, and PI) significantly predicted their TI in different academic contexts.

According to Zheng et al. (2022), language teachers’ ER enables them to deal with contextual stressors in the language classroom. As they explained, ER helps these teachers to consider their aroused emotions, evaluate their beneficial/detrimental effects on their performance, suppress the harmful emotions, and utilize the emotions that enhance their pedagogical effectiveness. Taylor et al. (2020) also found that English teachers who have higher levels of ER are aware of the situations associated with disturbing emotions and are able to adjust to the appropriate situations. It also helps teachers to use different stress management strategies to modify the negative emotions associated with certain classroom situations. Finally, ER helps teachers to divert their attention away from negative emotions and relieve their tension.

Moreover, Akbari (2007) stated that TR can enable English teachers to deal with stressful factors in the classroom as it boosts their academic confidence. He explained that TR educates teachers about their professional needs and helps them acclimatize to the demands of different teaching situations. It also enables teachers to build harmonious and functional relationships with their learners. Similarly, Farrell (2016) found that TR improves teachers’ psychological well-being as it enhances their classroom management skills, enables them to use effective assessment methods, boosts their self-confidence, and accelerates their self-management.

In addition, Yuan and Zhang (2020) found that English teachers’ PI is related to their mental health, mainly because it affects their self-assessment. According to them, the development of PI enables teachers to improve their self-awareness and recognize the underlying principles of their professional conduct. It also strengthens their pedagogical self-confidence and increases their intrinsic motivation to fulfill their tasks. Similarly, Xiang (2021) pointed out that PI relieves English teachers from most stressors in their environment as it makes them realize the value of their pedagogical performance, facilitates their goal setting, and minimizes their confusion about their role and related responsibilities in their environment.

In light of the above discussions, it can be said that the UK teachers’ ER was a significant predictor of their TI, as it made them aware of the debilitating effects of their negative feelings on their performance, helped them avoid stressful situations, and enabled them to divert their attention from the feelings that interfered with their optimal teaching performance. In addition, these teachers’ TR significantly predicted their TI as it improved their self-awareness and self-management and made them realize their academic capabilities, and empowered them to develop strong relationships with learners. Finally, the UK participants’ PI significantly determined the variance of their TI, as it boosted their self-confidence, accelerated their goal setting, improved their understanding of their professional behavior, and increased their intrinsic motivation.

The second question focused on the main predictors of Iranian English teachers’ productive and maladaptive TI. The results show that teachers’ income, age, and ER were the first, second, and third factors, respectively, that contributed most to explaining the variance in their TI. Overall, the results support the findings of Abbasi et al. (2018), Guerra-Bustamante et al. (2019), Kayed and Kazemian Moghadam (2021), and Zohrabi and Khalili (2023). These studies showed that English teachers’ personal factors (e.g. age and income) significantly predict their mental health.

Hanushek and Rivkin (2007) found that the income of English teachers is an important factor that can have a noticeable effect on their psychological well-being. According to them, the salary of teachers in most countries of the world is disproportionate to their knowledge, effort, and experience. In addition, a large number of these teachers rely on their income as their only permanent source of income. Consequently, the threat to English teachers’ income and their income-related insecurities may negatively affect their composure and increase their nervous tension. Similarly, Reardon and Portilla (2016) pointed out that the impact of income on English teachers’ mental health stems from the fact that it affects all aspects of their personal and social lives. As they noted, low-income teachers are prone to nervous breakdowns as they are constantly struggling with their financial problems.

In addition, Chetty et al. (2014) found that teachers’ age is likely to affect their psychological well-being. According to them, the insecurity of a group of teachers stems from their unfavorable perception of their teaching effectiveness. They explained that young teachers cope with these insecurities by relying on external support from their colleagues and certain experts such as teacher sneakers and supervisors. Nevertheless, the aging of teachers has a positive impact on their view of their pedagogical skills and leads to their professional maturation. That is, they become aware of their inner resources and shed their inhibitions by relying on these resources in the classroom.

Finally, Li et al. (2022) argue that ER is one of the crucial predictors of English teachers’ mental health. According to them, teachers may lack the ability to defuse their psychological tension stemming from various contextual stressors. As they explained, ER enables the teachers to resolve this kind of tension by monitoring their positive and negative feelings, evaluating the role of these feelings in their composure, and modifying their attentional resources to exploit their positive emotions for soothing the agony of the relevant stressors.

Based on these discussions, it can be concluded that the Iranian English teachers’ income was the most important factor in their TI as it affected all aspects of their lives and was a major source of their psychological tension. In addition, the age of these teachers significantly predicted the variance of their TI as it positively affected their professional maturation, made them aware of their teaching skills, and motivated them to use their inner resources to release their tensions. Finally, Iranian teachers’ ER was a significant predictor of their TI as it helped them suppress their negative feelings and utilize their positive feelings to improve their mental health.

The third question investigated the difference between British and Iranian English teachers’ productive and maladaptive TI. The results showed that the TI of British teachers was more productive than that of Iranian teachers. In addition, there were some differences between the factors in the TI of these groups of teachers. In general, these results underpin the results of the study that was carried out by Hiver (2017).

In his study, Hiver (2017) reported that TI is a context-dependent construct that reflects the causes of English teachers’ composure or distress. As he explained, the examination of the sub-components of TI shows that they may be influenced by numerous learner-related, context-oriented, and personal factors. He noted that the value that is placed on the language teaching profession in the society can affect the affectivity and attitudes towards teaching
sub-components of TI. Moreover, supervisors’ and colleagues’ feedback is likely to influence the burnout and teaching self-efficacy sub-components of this construct. Furthermore, teacher education courses may have an impact on the coping and openness to change sub-components of TI. Lastly, teachers’ access to professional counseling services may greatly influence the resilience sub-component of their TI in their relevant academic settings. In addition,
Xiyun, et al. (2022) pointed out that language teachers’ psychological well-being may be affected by their opportunities to participate in international events such as language-related conferences. Lastly, Li et al. (2022) argued that language teachers’ chances to take part in recreational activities can greatly influence their mental health.

In light of these discussions, it is possible to attribute the discrepancies between British and Iranian teachers’ TI types to the fact that their TI was influenced by different contextual factors. That is, there were differences between these teacher groups in terms of the social value of their profession, the peer support in their academic settings, the teacher education in their context, and the counseling that was provided to them during their service years.  In addition, the difference between the factors in these teachers’ TI can be attributed to the fact that British teachers have more opportunities to participate in international teacher training courses, conferences, and recreational activities compared to Iranian teachers.

Conclusion

This study investigated the main factors of productive and maladaptive TI of British and Iranian English teachers. The results show that British teachers’ internal resources (e.g. ER) were the most important predictors of their TI, while Iranian teachers’ income, which was an external factor, was the most important factor of their TI. These findings may have two obvious implications for teacher education programs in Iran. First, it is imperative to revise the curricula of these programs. Examining the curricula of most of these degree programs shows that they focus on teachers’ pedagogical skills and strategies and disregard their factors, including their TI. Consequently, it is necessary to add a specific teacher factor module to the relevant courses that inform instructors about teachers' affective and personal factors, including their ER, TR, PI, age, and income, and the relationships between these factors and their psychological health. It is also important to retrain the teacher educators of these courses. A large number of teacher educators are instructors who hold the teacher education position because of their experience or their various teacher education certificates. Therefore, they are mainly concerned with practical classroom considerations and are likely to disregard teacher factors such as TI. However, there is a need to provide them with teacher factor-based training to inform them about the importance of teachers' affective factors in language teaching. Teacher educators' knowledge of these factors can enable them to make prospective teachers aware of the affective strategies that can resolve their tensions.

Furthermore, the results may have clear implications for the training of supervisors in Iran. The study of supervisors’ duties shows that they are mainly responsible for conducting summative evaluations of teachers’ classroom performance. Nevertheless, it is clear from their job description that they have to provide emotional and psychological support to distressed teachers in their years of service. Consequently, the training courses for supervisors need to be revised by including a teacher factor module in them and making trainee supervisors aware of their responsibilities in relation to supervision and emotional support. In addition, it is necessary to provide supervisor sneakers with training based on psychological support. This kind of training can lead the sneakers to prepare the prospective supervisors to help the English teachers release their psychological tensions by utilizing their positive emotions.

This study had certain limitations as it did not examine the effects of participants’ gender and linguistic background on the results. In addition, the study was limited as it did not examine different academic data collection sites. Future research needs to address the above issues. It also needs to identify the factors of English teachers’ TI in different EFL and ESL contexts. Finally, future studies should identify the role of education-related factors such as teachers’ academic degrees and fields of study in their TI.

Acknowledgments

The authors express their gratitude to all of the individuals who participated in this study.

Declaration of Conflicting Interests

The authors declare that they have no conflict of interest.

Funding

This research study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.