Stress management intervention program for teaching staff at private engineering colleges in Tamil Nadu to improve their job performance and well-being

Purpose – Stress at workplace is quite common in all sorts of environment. It can be occurring when the demand in the job does not match with the requirements; thereby, it affects their performance. The study was conducted with the aim to identify the major factors that induce stress for teaching professionals in private engineering colleges and its impact towards job performance. From the observation and discussion, it was found that Workload, Working Hour, Salary, Role Ambiguity and Lack of Social Support are the major factors for stress. Design/methodology/approach – A structured questionnaire was framed with the help of stress-causing factors and their effect on job performance. In addition to this, a few questions were asked related to stress management intervention program. The survey was conducted with 370 respondents, while further analysis was carried out with the filled 260 respondent ’ s data using descriptive statistics, correlation, regression, ANOVA and SEM. Findings – The study reveals that workload plays a significant role in stress whereas other factors are consequently lower than that. Also, the primary-level intervention programs are more effective than secondary-level intervention programs to reduce the stress level of stressors. Originality/value – The paper was originally done by collecting data from the staff.


Introduction
Stress at workplace is unavoidable, but it may differ from one profession to another as well as the situation based on how individual/person tackles it.In general, teaching profession is considered as stress free profession.Due to rapid changes occurred in modern teaching pedagogy, technological advancement, expectation of management, career growth and survival, the teaching professionals are facing challenges in their profession (Olivier and Venter, 2003).The most common factors which create stress in workplace are workload, overtime, lack of recognition, misbehaviour of students, inadequate resource, role ambiguity and low salary (Borg et al., 1991).These factors affect teaching staff performance and productivity which leads to physical, psychological and behavioural effects.The physical symptoms include weakness, muscular tightness, headaches, heart tremors, sleeping disorder and constipation (Hakanen et al., 2011).Psychological symptoms include sadness, nervousness, dissuasion, petulance, glumness, being dazed and unable to manage, intellectual difficulties, such as abridged ability to make decisions (Hobfoll, 2011).Depression's behavioural symptoms include absenteeism, hostility, diminished creativity and inventiveness, poor job performance, marital problems, irritability, mood swings, an inability to tolerate hurdles, increased impatience and a sense of isolation (Mroczek et al., 2015).Even though many research studies has suggested and proven various stress management techniques, the present study focuses on to identify major stress-causing factor, symptoms, impact and remedial measures to overcome stress through primary, secondary and tertiary stress management intervention (SMI) techniques for the well-being of teaching staff.

Workplace stress and intervention techniques
Workplace stress can occur from the factors of work environment which affects an individual's psychological, physiological and behavioural conditions so that he/she cannot able to do normal activities (Newman and Beehr, 1979).The resulting negative outcome may impact their job performance.Ivancevich et al.' approach is enough to mitigate their unintended consequences (1990).There are three stages that make up the stress model: It is important to consider (a) the severity of stresses in the workplace, (b) the employee's assessment of stressful conditions and (c) the employee's resiliency while dealing with the outcomes.In an effort to reduce stress in the workplace, the authors of a study from 2003 (Murphy and Sauter) used three tiers of SMI: preventive, remedial and instructive.The objective of primary intervention technique is used to identify the sources which create stress and help to avoid it thereby providing well-being of an individual.A few examples of primary intervention programs are redesigning of job, authority for decision-making and co-workers' support (Kolbell, 1995).This strategy by Ivancevich et al. is sufficient to reduce the negative effects they may have (1990).The stress model consists of these three phases: It's crucial to take into account (a) the intensity of workplace pressures, (b) the employee's evaluation of those stresses and (c) the resilience of the person in coping with the results.The authors of a 2003 research (Murphy and Sauter) employed preventative, corrective and instructional SMI strategies to lower workplace stress.

Literature survey
Kekovi c et al. (2022) conducted a study with health workers in hospitals and identifies that 27 variables create stress for them.The study pointed out that inadequate personal income, work overload and misinformation of patients are considered as the major stress-causing factors.The study concludes as stress can be overcome through yoga, meditation and regular exercise practiced by the workers.Greif and Palmer's (2022) study was conducted to ascertain stress and stress management coaching.They come to the conclusion that changes in structural stress situations and resources like freedom of action and social support are the primary causes of stress.The studies all came to the same conclusion: time management, relaxation and mindfulness exercises are the best ways to reduce stress.Eddy et al.'s (2022) study used bibliotherapy-based stress management training program for teachers using a control group size (N 5 52).The study identifies that the intervention program supports the teachers to reduce stress and mental health symptoms.The study also finds that the program did not help the teachers to improve job satisfaction.However, it is recommended to provide a few feasible programs to improve satisfaction and well-being.Dodanwala et al. conducted a study on workplace stress and work-life conflict (2022).Three hundred and eight members of the project personnel in Sri Lanka were surveyed using a predesigned questionnaire.The findings indicate that role and time demands contribute most to mental and physical exhaustion on the job.Both introducing a primary intervention

SMI program for teaching staff
program and providing employees with extra time to cope with stress were shown to be beneficial in the study.Meng and Wang (2018) conducted a study on occupational stress of teaching staff in a university with a sample size of 240 respondents in China.The study identifies work overload, working hours and lack of support from co-workers as stress-causing factors in the university.The study suggested providing primary-and secondary-level intervention programs to the staff for their well-being.H2.Occupational stress leads to negative impact on job performance.

Objectives of study
H3.Primary and secondary stress management techniques help reduce stress and provide well-being.

Correlation analysis
The coefficient of correlation between workload, working hours, salary, social support and role ambiguity with occupational stress is well explained in Table 2.It describes workload, working hours and role ambiguity as being positively correlated with occupational stress, and the values obtained through the analysis are 0.950, 0.662 and 0.684.Occupational stress is caused first by workload, next by job uncertainty and last by the number of hours worked.When compared to occupational stress, however, both salary and social support were shown to have negative correlations (À0.885 and À0.906, respectively).Our research shows that teachers of engineering at private universities are more likely to experience occupational stress if they meet these five characteristics.Tables 3-5 provide summaries of the primary intervention program and the secondary intervention program, respectively, in the context of occupational stress.Inferred from the aforementioned data are the correlation coefficients of À0.85, À0.87 and À0.835 between occupational stress and the effectiveness of the faculty, the primary intervention program, and the secondary intervention program, respectively.It denotes that the teaching staff cannot perform well on the job due to occupational stress, whereas the intervention program supports them to reduce the stress.

Regression analysis 9.1 Factors causing occupational stress
Regression is a statistical tool used to build a model and examine the relationship between dependent and independent variables.This analysis is used to determine the degree of    In this case, we will continue our inquiry only if R is less than or equal to 0.4.The quality of this order is represented by a value of 0.957.The coefficient of determination, or R2, reveals what fraction of total variation in the dependent variable can be pinned on the independent factors.With an R-squared value greater than 0.5, we may infer that the model is sufficient for discovering the association.Also of very good quality is the situation's R-squared score of 0.916.Adjusted R-square in multiple regressions shows how representative the sample data is of the whole population, or how much variation there is between the sample and the overall results.Adjusted R-squared values must be higher than R-squared at a bare minimum.Given how close it is to the ideal of 0.916, the price of 0.915 is a steal.SPSS's second table of a regression analysis is where model significance testing takes place.p-value/sig value: Researchers often use either a 95% confidence interval or a 5% criterion of significance in their studies.This means that we may safely assume that the p-value is rather small (0.05).The first entry in the table at the top of this page is numbered 001.This accounts for the significance of the result.
F-ratio: The accuracy with which a model makes predictions about a given variable is evaluated.A number greater than one indicates that the model is effective and has a high F-ratio yield., reveals what fraction of total variation in the dependent variable can be pinned on the independent factors.If the coefficient of determination (R) is more than 0.5, then the model is sufficiently fit to detect the association.Also respectable is the R-squared value of 0.722 found here.Adjusted R-square in multiple regressions shows how representative the sample data is of the whole population, or how much variation there is between the sample and the overall results.Adjusted R-squared values must be higher than R-squared at a bare minimum.To be honest, 0.721 is not perfect, but it's not far off from the optimum number of 0.916, either.The second table of a regression analysis in SPSS is used to assess the significance of a model.p-value/sig value: Researchers often use either a 95% confidence interval or a 5% criterion of significance in their studies.This means that we may safely assume that the p-value is rather small (0.05).The first entry in the table at the top of this page is numbered 001.This accounts for the significance of the result.F-ratio: It is a quantitative evaluation of a model's ability to accurately forecast the target variable.An F-ratio greater than one indicates a successful model with a high predictive yield 671.102 seems to be a good estimate based on the information provided.Reduced output is a well-known consequence of stress in the workplace.9.3 Primary intervention program vs. occupational stress H03.Primary intervention program has positive impact on occupational stress.
HA3.Primary intervention program has negative impact on occupational stress.8, which is generated before any other table during a linear regression analysis, provides a thorough description of the model's characteristics.Currently, only factors related to the primary intervention program are considered.When comparing two variables, the R-value shows how strong that link is.The R-value here, at 0.870, is acceptable.The coefficient of determination, or R2, reveals what fraction of total variation in the dependent variable can be pinned on the independent factors.If the coefficient of determination (R) is more than 0.5, then the model is sufficiently fit to detect the association.As an extra measure of quality, the 0.757 R-squared value in this case is fine as well.Adjusted R-square in multiple regressions shows how representative the sample data is of the whole population, or how much variation there is between the sample and the overall results.Adjusted R-squared values must be higher than R-squared at a bare minimum.Our result of 0.756 is rather good, and it's not far from the perfect value of 0.916.SPSS has a second table for a regression test, which is used to examine the predictive power of a model.

SPSS's Model Summary Table
p-value/sig value: Researchers often choose a 95% CI or a 5% p-value criterion.That means the p-value cannot be higher than 0.05.The value 0.001 represents this in the aforementioned table.The discovery is significant.HA4.Secondary intervention program has negative impact on occupational stress.
Table 9 indicates the regression analysis in SPSS, the first step is to generate a detailed description of the model in a table called the Model Summary.Considerations unique to the secondary intervention strategy are now under scrutiny.R-value represents the strength of the relationship between the two variables.We have a respectable R-value of 0.835.The amount of variation in the dependent variable that can be ascribed to the independent variables is represented by the R-squared statistic.For a model to be able to make the association, the coefficient of determination (R) must be greater than 0.5.Similarly, the 0.697 R-squared value is acceptable here.The Adjusted R-square in multiple regressions shows how close the results are to those obtained using a single regression, or how much variation there is between the sample and the population.Adequately adjusting for R-squared is required.This situation is good enough with a 0.696 value.SPSS's second table in a regression test one examines whether the model is statistically significant enough to predict the result.p-value/sig value: Research often uses a 95% confidence interval or a 5% criterion of significance.Therefore, the p-value has to be much below than 0.05.A value of 0.001 represents this in the aforementioned table.This is a really significant result.
F-ratio: This measure of the model's performance improves the predictability of the variable in question.An efficient model with a positive F-ratio yield has value larger than one.The coefficient for Workload in this situation is 0.466, showing Workload's partial contribution assuming no change in other Occupational or Workplace Stressors.Both the expected positive sign and the coefficient value are significant at the 1% level, indicating that increased workload does indeed lead to increased occupational/workplace stresses.When controlling for other stressors in the workplace, the coefficient for Lack of Social Support is 0.201, indicating a moderate level of effect.For example, the predicted positive sign suggests a positive influence, and the coefficient value is significant at the 1% level, suggesting that stress in the workplace increases by one unit for every one point increase in Lack of Social Support.The coefficient of Working Hour is 0.004, indicating that Working Hour has only a little impact when all other occupational and workplace stressors are controlled for.This coefficient value is statistically significant at the 1% level, and its negative sign suggests a negative effect, implying that occupational/workplace stresses will decrease with each unit decline in Working Hour.If all SMI program for teaching staff other factors in a job or workplace remain the same, income may be a significant motivating factor (coefficient of 0.320) shown in Table 10 and Figure 1.
According to the predicted significance level of 1%, the positive sign of the coefficient value indicates that occupational/workplace stressors will grow with each unit increase in salary.Assuming that Occupational and Workplace Stressors remain unchanged, the coefficient for Role Ambiguity is 0.069 and shows the moderate impact of Role Ambiguity.Since the calculated coefficient value is positive and significant at the 1% level, this suggests that a rise in Role Ambiguity has a favourable influence on occupational and workplace stressors.When Occupational/Workplace Stressors are held constant, the coefficient for Primary Intervention Techniques is 0.014, indicating the technique's partial impact.Indicating a positive impact, the calculated coefficient value of 1.01 suggests that occupational/workplace stressors would rise with each unit increase in primary intervention techniques.With occupational and workplace stressors held constant, the coefficient for secondary intervention techniques is 0.273, showing a partial influence of these techniques.Since the calculated coefficient value is positive and significant at the 1% level, it follows that the addition of secondary intervention techniques has a favourable influence on occupational and workplace stressors.When Job Performance and Employee Well-Being are held constant, the coefficient for Occupational/Workplace Stressors is 0.168, representing the partial influence of Occupational/Workplace Stressors.If the calculated coefficient value is positive, then the relationship between occupational/workplace stressors and job performance and employee well-being is positive and statistically significant at the 1% level.
As can be seen in Table 11, the estimated p-value of 0.000 is lower than the significance level of 0.05, suggesting a perfect match.It is clear that there is a good match between these two variables since both the GFI and the AGFI are more than 0.8.Root Mean Square Residual 5 0.071 and Root Mean Score Error of Approximation 5 0.059, both less than 0.10,

SMI program
for teaching staff over 0.40.The internal consistency of all variables indicated that all items endured well with the internal consistency of 0.720 while the variables with the topmost validity are "Enhance the teamwork", "Highly effective tasks" and "Increase efficiency in process" which were represented in Figure 3.  10.4 Confirmatory factor analysis for employee well-being Table 15 enumerates the values of validity assessment of the EWB Instrument questionnaire item-wise.Meanwhile, the CFA value of "Occupational Stress" falls between 0.790 and 0.960, there are no items deleted as the values have fulfilled the requirement of over 0.40.The internal consistency of all variables indicated that all items endured well with the internal consistency of 0.790 while the variable with the topmost validity is "I am satisfied with my organization's overall wellness offerings" as demonstrated in Figure 5.

Conclusion
Research focused mostly on how workplace stress affects productivity.Workload was shown to be the single most influential factor in determining employee output.All workers clearly and significantly decreased their output as a direct effect of work-related stress.The study's findings show that employees of both sexes experience stress in the job.Workers of all ages agree that stress in the workplace has a deleterious effect on efficiency.It is the duty of each given company to aid its workers in managing the stress they inevitably encounter on the job.In order to combat stress, primary-and secondary-level intervention programs and other stress management strategies have been implemented.

( 1 )
To study the factors causing workplace stress (2) To identify the level of workplace stress with respect to demographic variables (3) To analyze the relationship between stress-causing factors and job performance (4) To implement the SMI techniques which helps to overcome stress and provide wellbeing 5. Research hypothesis H1.Workload, working hour, salary, role ambiguity and lack of social support have impact on occupational stress.
): **Correlation is significant at the 0.01 level (2-tailed) Source(s): Figure 3. Measurement model of SLSMP instrument Figure 5. Measurement model of EWB instrument Table by authors Table 1.
Table by authors between two sets of data.Methods of hypothesis testing are used for this purpose.The hours worked, salary, social support and job uncertainty are all independent variables that contribute to the dependent variable of occupational stress.After that, we may propose the following research hypothesis:H01.Factors such as workload, working hours, salary, social support and role ambiguity do not impact occupational stress.HA1.Factors such as workload, working hours, salary, social support and role ambiguity impact occupational stress.SPSS's Model Summary Table6, which is generated before any other table during a linear regression analysis, provides a thorough description of the model's characteristics.We paid special attention to issues of position ambiguity, long hours, low income, high stress and a lack of social support.When comparing two variables, the R-value shows how strong that link is. similarity The total of 556.15 in the table meets expectations.A person's level of stress is influenced by several factors, including the nature of the work, the number of hours put in, the salary, the availability of social support and the degree of clarity around the individual's role in the organization.Occupational stresses do not impact job performance of staff.SPSS's Model Summary Table7, which is generated before any other table during a linear regression analysis, provides a thorough description of the model's characteristics.Here, job performance is the fundamental criterion for assessment.When comparing two variables, the R-value shows how strong that link is.Having an R rating of 0.850 is really high.The coefficient of determination, or R2 occupational The accuracy with which a model makes predictions about a given variable is evaluated.A number greater than one indicates that the model is effective and has a high F-ratio yield.Towards the top of the chart, you'll find a rock-solid sum: 803.21.Evidence like this suggests the primary intervention strategy was effective in reducing stress in the workplace. F-ratio: There's good news: the figure in the table above is 594.884.That's why it's important to have secondary intervention programs that work to lessen stress in the workplace.

Table 11 .
Table by authors; Statistically analyzed data Table12enumerates the values of validity assessment of the PLSMP Instrument questionnaire item-wise.Meanwhile, the CFA value of "Primary-Level Stress Management Program" falls between 0.720 and 0.990, there are no items deleted as the values have fulfilled the requirement of over 0.40.The internal consistency of all variables indicated that all items endured well with the internal consistency of 0.720 while the variable with the topmost validity is "Greater job satisfaction" as shown in Figure2.10.2Confirmatory factor analysis for Secondary-Level Stress Management ProgramTable13enumerates the values of validity assessment of the SLSMP Instrument questionnaire item-wise.Meanwhile, the CFA value of "Secondary-Level Stress Management Program" falls between 0.720 and 0.990, there are no items deleted as the values have fulfilled the requirement of Table by authors; Statistically analyzed data Model fit summary

Table 12 .
Table by authors; Statistically analyzed data Summary table of validity results of PLSMP instrument Table by authors; Statistically analyzed data

Table 13 .
Summary table of validity results of SLSMP instrument

Table 14 .
The stress alleviation program, whichTable by authors; Statistically analyzed data Summary table of validity results of OS instrument includes mindfulness training, resilience training, psychological intervention and behavioural intervention, is put into practice and appears to be quite effective at enhancing employees' job performance.