|Year : 2019 | Volume
| Issue : 3 | Page : 150-155
Level of stress among schoolteachers of a school in South Delhi, India
Mamta Parashar1, Deeksha Ellawadi2, Mitasha Singh3, Ram Chander Jiloha4
1 Department of Community Medicine, Hamdard Institute of Medical Sciences and Research, Jamia Hamdard, New Delhi, India
2 Department of Psychiatry, Hamdard Institute of Medical Sciences and Research, Jamia Hamdard, New Delhi, India
3 Department of Community Medicine, ESIC Medical College and Hospital, Faridabad, Haryana, India
4 Department of Psychiatry and Rehabilitation Sciences, Hamdard Institute of Medical Sciences and Research, Jamia Hamdard, New Delhi, India
|Date of Submission||11-Jun-2018|
|Date of Decision||16-Dec-2018|
|Date of Acceptance||08-Mar-2019|
|Date of Web Publication||13-Aug-2019|
Department of Community Medicine, ESIC Medical College and Hospital, Faridabad, Haryana
Source of Support: None, Conflict of Interest: None
Background: Modernization and increasing level of competition in day to day life has increased the expectations from teachers. Objective: To describe the level of stress and its associated factors among teachers using Teacher's stress inventory in a government school of urban area of South Delhi. Methods: A cross sectional study among teachers of a senior secondary school located in south Delhi. This was part of mental health literacy workshop conducted March 2017. 124 teachers attended the same and 94 participated in the study. Teachers' stress inventory scale was used as a tool to assess the level of stress along with demographic factors of the study participants. Only 82 completed questionnaires were included in analysis. Results: The mean score among discipline and motivation sub category was a significantly higher source of stress among young age teachers (P <0.001). The mean scores among females were higher as compared to males among the sources of stress however the difference was not statistically significant. Joint family was a significant stressor source especially under professional distress in bivariate analysis (P: 0.04). As the experience duration increased the mean stress score also increased (correlation coefficient: 0.10, P: 0.36). All the variables were subjected to multiple linear regression models and it was found that gender, education and family income are significant predictors with stress as dependent variable. Conclusion: The social and economic instability cut across all ages and increase the risk of stress and burnout.
Keywords: Metro city, teachers' stress inventory, workplace
|How to cite this article:|
Parashar M, Ellawadi D, Singh M, Jiloha RC. Level of stress among schoolteachers of a school in South Delhi, India. CHRISMED J Health Res 2019;6:150-5
|How to cite this URL:|
Parashar M, Ellawadi D, Singh M, Jiloha RC. Level of stress among schoolteachers of a school in South Delhi, India. CHRISMED J Health Res [serial online] 2019 [cited 2019 Oct 17];6:150-5. Available from: http://www.cjhr.org/text.asp?2019/6/3/150/264381
| Introduction|| |
Stress is an unavoidable and unpleasant experience which affects everybody in different ways and at different times. It is difficult to define. Selye originally suggested that stress is simply the rate of wear and tear in the body. The World Health Organization (WHO) Global Burden of Disease Survey estimates that by the year 2020, stress-related mental health conditions will be the second most prevalent after ischemic heart diseases.
Teachers are a priority population as they are role models for students and influential members of society, capable of influencing overall development of students. According to reviewed literature, Kyriacou and Sutcliffe defined teachers' stress as an uncomfortable feeling, negative emotion such as anger, anxiety, pressure, and disappointment sourced from their work aspects as a teacher. Besides this, Johnson et al., in 2005, concluded that out of 26 professions, teaching represents the second most stressful occupation after ambulance car drivers. The WHO has identified workplace experiences as one of the factors determining well-being. A negative environment at workplace leads to physical and mental health problems.
The previous literature from different parts of the country have tried to explore in this area either through a single-centric or multicentric study. Studies from South India among university teachers and schoolteachers in Rajasthan used self-reported stress to report the presence or absence of stress.,, Dawn et al. from West Bengal, Pokhrel from Sikkim, Hasan from Haridwar, and Jeyaraj et al. from Madurai have used different scales to measure stress among either male or female teachers of various grades belonging to rural and urban areas.,,, There are methodological differences among all studies. However, until we do not have a nationwide survey or uniform scale, every study adds evidence to the existing literature. Exploring the magnitude of stress and associated factors among teachers can contribute to the development of preventive and control strategies for stress management at local level.
In the present study, we have attempted to describe the level of stress and its associated factors among teachers using teacher's stress inventory in a government school of urban area of South Delhi.
| Methodology|| |
It was a cross-sectional study.
This study was conducted in a government school located in South Delhi. It was selected owing to the convenience of proximity to the institute. This study was part of a workshop on mental health literacy on the occasion of World Mental Health Day, 2017.
Ethical approval and study subjects
Prior ethical approval was sought from the institute's ethical committee. Investigators were aware of the ethics in biomedical research policy of the Indian Council of Medical Research (2006) and Declaration of Helsinki revised in 2002. Keeping in view, written informed consent of all participants was obtained before gathering any information. The information collected is kept strictly confidential, and individual identity will not be disclosed under any circumstance. The study involves no risk to the subject and involves no financial burden.
Schoolteachers of Classes 1–12 were enrolled from the above school. Those who have worked at least 50% of fulltime during 6 months before completion of the questionnaire were included in the study.
In a study on schoolteachers in Varanasi, Singh and Singh  found that about 42% of them had “high” to “very high” level of stress and were at higher risk of developing psychosocial stress-generated problems. At 42% prevalence, 10% precision, and 95% confidence interval, the minimum sample calculated is 94.
Sampling and data collection
There were 126 teachers in the school. The survey was conducted on the teachers participating in the mental health literacy workshop for 2 days during vacation time in school only. Permission was obtained from the head of the school. Convenience sampling was used. All were invited, of which 124 attended the workshop. Of these, 28 were on ad hoc service who did not meet our inclusion criteria to study stress. All the teachers were included in the workshop.
Of the 124 study participants, 3 did not consent to participate as they admitted that they are not comfortable with the language of the questionnaire. Anonymity was maintained by asking them not to write their names in the questionnaire. The filled-in questionnaires were collected back from them on the same day before the start of the workshop.
A predesigned structured pro forma in English language was introduced to obtain the sociodemographic details after explaining the purpose of the study to the participants and taking consent. The teacher stress inventory  is composed of 49 stress-related and 9 optional demographic items and takes about 15 min to complete. The five stress source factors are time management, work-related stressors, professional distress, discipline and motivation, and professional investment; the five stress manifestations factors are emotional manifestations, fatigue manifestations, cardiovascular manifestations, gastronomic manifestations, and behavioral manifestations. The respondent completes the inventory by circling the appropriate answer on the 1–5 rating scale, then summing and dividing scores. It consists of 10 subscales, each subscale being composed of three to eight items. The five stress source and five stress manifestation subscale scores are summed and divided by 10 in order to derive a total stress score. Higher score is considered as higher level of stress.
Data and statistical analysis
The baseline questionnaires were returned by 121 participants, and the returned questionnaires were checked by the investigators for completeness. The filled questionnaires of 28 teachers who did not meet the inclusion criteria were excluded during the analysis. Only 82 questionnaires were found to be complete and hence were included in the final analysis.
Age of participants was divided into two groups, namely young age (<40 years) and middle age (41–60 years). The highest level of education attained by participants was categorized into those who have completed graduation, postgraduation, and Master of Philosophy (M. Phil.) or Doctor of Philosophy (Ph.D.). The level of students teachers were teaching was categorized into elementary (5th class and below), middle school (6th–9th), and secondary and higher secondary (10th–12th).
The subscale and total scores were stratified among various independent variables and presented in the form of mean. For comparison of mean scores, t-test and analysis of variance were applied after checking for normality of the distribution of data. Level of significance was set at 5%. Multiple linear regression (MLR) model was run to identify predictors of stress. There were no outlier and autocorrelation in our regression data, and the assumption for normality and homoscedasticity was met. Statistical analysis was done using the Statistical Package for Social Sciences (SPSS) version 21 (IBM Corp., Armonk, NY, US).
| Results|| |
The subscale contains stress sources and its manifestations under different heads. The mean score of time management, work-related stressors, and discipline and motivation as sources of stress was higher among younger age group. Among the above, discipline and motivation was a significantly higher source of stress among young age teachers (P < 0.001). The mean scores among females were higher as compared to males among the sources of stress; however, the difference was not statistically significant. Joint family was a significant stressor source, especially under professional distress in bivariate analysis (P = 0.04). The mean score of time management as a source of stress was observed to be increasing significantly as the level of education of teachers increased (P = 0.01). The scores of time management indicated increasing stress among unmarried and divorced teachers (P = 0.02). Family income was significantly distributed among different sources of stress. Lower the family income higher the mean score of stress sources. There was no apparent trend among the mean scores of sources of stress in terms of different grades of students the teachers used to teach [Table 1].
|Table 1: Sociodemographic distribution of mean score of source of stress|
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The distribution of subscale stress manifestation scores shows that the mean score of fatigue was significantly higher among females (P = 0.02) and higher education status of teachers (P = 0.03). The cardiovascular, gastronomic, and behavioral scores were significantly higher among females as compared to males [Table 2].
|Table 2: Sociodemographic distribution of mean score of manifestation of stress|
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The total mean score of stress among study participants was 2.32 (±0.54). About 9.8% of the teachers were stressed. Overall mean stress scores were significantly higher among females and teachers with low family income [Table 3]. The mean years of experience of study participants was 14.45 (±8.93). As the experience duration increased, the mean stress score also increased (correlation coefficient: 0.10, P = 0.36). There was a negative correlation of the duration of experience with time management, work-related stressors, and discipline and motivation. Only emotional manifestation of stress decreased as the years of experience increased; however, this correlation was not statistically significant. Other manifestations were positively correlated with experience. None of the subscale scores' correlation with experience was statistically significant.
All the variables were subjected to MLR and it was found that only gender, education, and family income are significant predictors with stress as a dependent variable. Family income had a higher impact as compared to gender and education by comparing standardized coefficient (beta) (−0.44 for family income, 0.39 for gender, and 0.25 for education) [Table 4].
|Table 4: Multiple linear regression models to identify predictors of stress|
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| Discussion|| |
There has been a paradigm shift in the roles of teachers and societal expectation in the last decade. The teachers have moved from the role of a formidable “guru” to someone who can be evaluated, assessed, and questioned. In addition, the demands from school organizations and the race of the modern life have added to an increase in the stress levels of teachers. The stressful conditions faced in a teacher's daily routine may lead to an imbalance between work and physical and mental health, resulting in the development of stress.,
The proportion of stressed teachers in our study was 9.8%. This was comparable to 12.4% reported by Dawn et al. and 15% by Chaly and Anand. Majority of other studies reported mean score in different domains of the scales used by them., In our study on investigating the factors associated with stress, age was found to be a significant contributor. Teachers in the younger age groups had higher stress levels than their older counterparts. This can be due to greater pressure to perform in the early stages of the career. A few studies in the past have also shown evidence of better coping, with increasing age.,, In another all-female teacher study from India, it was found that married older teachers with higher experience cope better. Contrasting results were reported by Dawn et al. from West Bengal, Manjula from Kodaikanal, and Qadimi et al. from Mysore with higher age group reporting more stress.,,
Time management, work-related stressors, and discipline and motivation were the main sources of stress in the younger population. Similarly, in another cross-sectional study from India, time management and work-related stressors were the more common sources of stress with feelings of fatigue and emotion-related symptoms being the common manifestations of stress., The stress score was higher among higher grade teachers; however, there was no significant difference. Dawn et al., in their study, also mentioned teachers of higher grade being more stressed.
There were no significant differences observed in the stress levels between male and female teachers. However, the physical and psychological manifestations of stress were found to be higher in the female teachers. Similar findings were reported by Dawn et al. and Klassen and Chiu, where female teachers were more stressed than males; however, this did not amount to mental ill health., The individual differences in stress reactivity are often attributed to the hypothalamic–pituitary–adrenal (HPA) axis. HPA response patterns are markedly different between the two genders; therefore, there is an increase in the bio-psycho-social consequences of stress in females. The most common consequences of stress were anxiety, headache, irritability, and disturbed sleep.
Lower family income emerged to be an independent risk factor for stress. It was more strongly associated with stress than age and gender. An inverse relation was observed between income and stress. Dawn et al. gave contrast results of higher stress among more paid teachers. Their reason for the above finding was that the administrative postholders earning higher salary are more stressed. However, they considered individual salary and we included the family income.
It is difficult to comment on the direction of causality in this case, as this was a descriptive study. In addition, lower socioeconomic status can lead to other risk factors such as poor nutrition and housing which can, in turn, lead to stress. Similar studies even from the developed countries have shown stressful conditions in the workplace to be directly related to a low monthly income. The social and economic instabilities cut across all ages and increase the risk of stress and burnout.
This study is one of the few studies from India assessing the level of stress in schoolteachers. The limitation of the study being a survey with the possibility of socially appropriate responses should be borne in mind. Furthermore, a single-centric study cannot generalize our findings still it gives insight of the problem. In addition, there might be a fear in the minds of teachers regarding job loss in case of higher stress levels or serious psychological problems. No inferences can be drawn on the causality of stress. The study has given some insights in the reasons and consequences; however, in-depth interviews may be a more useful in identifying the locus of concern.
| Conclusion|| |
Stress in many cases has been considered a normal accompaniment of life, however if not tackled can lead to many psychological and physical health problems. Therefore, it becomes important to assess for stress in teachers who are the guardians of a country's future and include them in the school mental health programs ensuring their well-being.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4]