Positive mental health on Indian track: A complex twist of occupational stress and coping.

Background: The present research aimed to propose a positive mental health model in relation to occupational stress and coping styles among train drivers of Indian railways.
Methods: Sample (N = 300) in the age group of 21-59 years, with 40 years of mean age, and the job experience ranged from 3 to 40 years with a mean of 15 years was undertaken through purposive sampling technique. The sample also had a proper representation of the sociodemographic background. The survey-based research design with an empirical approach was used in the present study.
Results: The structural equation model revealed the positive mental health of train drivers negatively associated with the experience of occupational stress. Their flourishing state has supported the positive effect of problem-focused coping and the negative effect of social support. However, this relationship with work stress was absent. Through moderation effect, problem-focused coping style strengthens the inverse association between occupational stress and positive mental health. This effect was equivalent across all living areas and income groups at the model as well as the path levels. Conclusions: This study revealed that train drivers who engaged in problem-focused coping could better handle organizational role stress and benefit from improved mental well-being. Therefore, many failures in the railway caused by human error emphasize the importance of this preventive strategy. Copyright:

Indian railway has grown substantially in the past decades with greater network and tracks length. However, there has been a growing concern that mental health issues among frontline personnel such as train drivers have not been addressed satisfactorily. Train operation is a complex, sociotechnical system that involves various cognitive demanding tasks of continuously monitor the surrounding environment, maintain awareness, process information, and make decisions under risk. They experience different levels of mental workload during the routine and nonroutine driving conditions, resulting in mental strain on them can negatively affect their performance and the human-machine system's interaction.[1] They perform duties as per the continuous roster implies that they do not have rest provision like other employees. They usually need to work for 10 h per shift. They can demand replacement after this period, which should be done 2 h before the need.[23] Numerous studies have examined the association between working hours and work stress,[4] its negative consequences such as increased hazard rate and coronary heart disease,[5] and fatigue due to degraded sleep quality resulting from split rest periods obtained before the duty.[6] In addition, changes in unsocial working hour characteristics have consistently associated with parallel changes in work-life conflict[7] and depressive symptoms.[8]

The train operation is mainly governed by timetables and technical conditions such as the type of trains and track area restrict the driver's ability to execute the job.[9] The literature provides a wide range of information concerning the relationship between job autonomy and work stress and its impact on employee behavior.[101112] Furthermore, railways are introducing advanced technologies day by day. Therefore, train drivers have to cope with the strain resulting from transferring existing knowledge to this new technology. It can affect the modalities for employees functioning, thus slowing adoption and changes,[13] constitute a major source and risk of prolonged work stress experience resulting in burnout.[14]

The prolonged working on the train would also reduce work efficiency and lead to psychosomatic diseases.[15] Besides, acute psychosocial stress also impacts an impairment of a broad range of cognitive and emotional functions, including decision-making and prolonged abnormalities in attention and memory.[16] These functions are crucial in the job of a train driver responsible for the safety of many lives. Therefore, for this purpose, optimal work capacity is required.[17] Similarly, prolonged working conditions proved harmful effect on job demand and job satisfaction including other health parameters such as short sleep duration, tiredness after work, and metabolic parameters correlated with work stressors,[18] leads to the common symptoms of burnout, exhaustion accompanied by depression, and anxiety.[19] Apart from this, the actual evolutionary processes such as sudden changes in the customer's demand, management, increase in financial requirements, public opinion pressure, and growing competition have contributed explicitly or implicitly to stable, recurrent, and excess stress to the train drivers costing very high to the organization.[20] Therefore, in this context, the detection of long-lasting stress in its early stage may allow the prevention of irreversible well-being damages.[21]

Work is an essential factor in mental health and well-being outcomes,[22] as employees occupy about one-third of their own time at the job and need not be leave work back when they come out from the worksite.[23] In light of these facts and under the nature of train drivers work, these job characteristics may evolve into stress by damaging coping mechanisms either at work or outside work. In addition, they work in shifts face difficulties in family life and tend to restrict their social and leisure activities.[24] It can affect overall well-being and negatively impact work performance.[25] Moreover, failure to manage the well-being and work-life balance of train drivers may increase the risk to train safety and their mental health. Therefore, improvement in it benefits their overall health and reduces the risk of train safety problems.[2627] Furthermore, various research on job stress demonstrated that prolonged exposure to chronic stressors and unsuccessful coping impacts employees’ well-being.[282930] Given this, the objective of the present study was the exploration of the positive mental health model of train drivers of the Indian railway.

METHODS

Participants

The homogeneous sample of 300 train drivers of Indian railways was collected through the purposive convenience sampling technique. The sample consisted of participants with 40 years of mean age ranged from 21 to 59 years old, and the job experience ranged from 3 to 40 years, with a mean of 15 years. The description of the sample has been demonstrated in Table 1, with other relevant specificities of the current investigation in Table 1.

Table 1

Sociodemographic characteristics of the sample (n=300)

Characteristic	Proportion	95% CI
		Lower	Upper
Education
SSC*	0.050	0.028	0.081
HSSC†	0.047	0.026	0.077
ITI‡	0.417	0.360	0.475
DIPLOMA§	0.293	0.242	0.348
Degree	0.147	0.109	0.192
Postgraduate	0.047	0.026	0.077
Living area
Urban	0.427	0.370	0.485
Suburban	0.437	0.380	0.495
Rural	0.137	0.100	0.181
Income (in rupees)
Low	0.623	0.566	0.678
High	0.377	0.322	0.434

*SSC (10 years of schooling); †HSSC (12 years of education); ‡ITI. It is a training organization responsible for providing industry-related education. The length of courses is mostly 2 years with the eligibility of SSC; §DIPLOMA – 3 years course of electrical or mechanical engineering with the eligibility of SSC. SSC – Secondary School Certificate; HSSC – Higher Secondary School Certificate; ITI – Industrial Training Institute; CI – Confidence interval

Procedure

The selected sample among the train drivers was contacted personally at their respective training institutes. The purpose of the study was explained to them. The communication was also provided regarding their willing participation and withdrawal from the study at any moment. Their written consent was sought for participating in the research. After assuring about the anonymity of the responses, all the scales were distributed to them. Although all the scales were self-administered, instructions were read out to them for the sake of clarity. While collecting the scales back, train drivers were provided with the opportunity to express their views on any aspect of the study. In the end, their participation was appreciated by expressing thanks for taking precious time.

Measures

Keyes[31] Mental Health Continuum (MHC)-Long Form was used in this present study. It is a self-administered scale consisting of emotional well-being, which includes six items of positive affect scale on 5-point rating scale and a life satisfaction scale with a single item. There are 18 items assessing psychological well-being and 15 items of social well-being, both on 7-item point rating scale. Internal reliability estimates were found to be high > 0.80 for this long form, and it was. 81 for the overall psychological and social well-being domain and. 91 for the emotional well-being domain.

Srivastava and Singh[32] developed the occupational stress index (OSI) was used in the present study. This index consists of 46 items comprising almost all substantial elements of work life on the 5-point rating scale, which cause job stress. It comprises role overload, role ambiguity, role conflict, group and political pressure, responsibility for persons, under participation, powerlessness, poor peer relationship, intrinsic impoverishment, low status, unprofitability, and strenuous working conditions. Cronbach's alpha coefficients and split-half reliability were found to be 0.90 and 0.93, respectively.

The revised ways of coping checklist (WOC-R) were used in the present study developed by Folkman and Lazarus.[33] This scale consisted of 42 items on a 4-point rating scale measuring eight dimensions which can be clubbed into three factors: problem-focused coping (consisting of 11 items), emotion-focused coping (24 items covering dimensions of wishful thinking, distancing, focusing on the positive, self-blame, tension reduction, and self-isolation), and social support (seven items on the dimension of seeking social support). The reliabilities (‘s) of eight scales were averaged over three occasions, and the results ranged from 0.56 to 0.85.

RESULTS

Data screening was done through box plots, Q-Q plots, and visual examination of the normal probability curve after eliminating the observed outliers. In addition to this, skewness, kurtosis, Shapiro–Wilk test, homogeneity of variances, multicollinearity, linearity, and homoscedasticity test were also applied to test the normality of data as well as further assumptions of statistical treatment. Table 2 demonstrates descriptive statistics and reliability analysis of all studied variables for the composite samples. In aggregate, the mean score revealed that train drivers were on a higher echelon of positive mental health including its three dimensions of well-being, occupational stress, problem-focused coping, emotion-focused coping, and social support.

Table 2

Descriptive statistics and reliability analysis of the major study variables

Variable	Item	Mean	SD	Obtained		Obtainable		Alpha (α)
				Minimum	Maximum	Minimum	Maximum
PMH‡‡	40	194.97	27.42	124.00	257.00	39	271	0.83
EWB	7	26.33	6.44	9.00	40.00	06	40	0.84
PWB	18	95.38	13.49	58.00	126.00	18	126	0.70
SWB	15	73.37	13.97	40.00	105.00	15	105	0.70
OS	46	148.70	25.70	78.00	208.00	46	230	0.91
Coping	42	72.27	14.38	38.00	108.00	00	168	0.84
PFC	11	20.53	4.73	9.00	33.00	00	33	0.73
EFC	24	39.77	9.32	20.00	63.00	00	72	0.71
SS	7	11.97	3.62	2.00	21.00	00	21	0.76

‡‡PMH is the addition of Emotional, Psychological, and SWB. PMH – Positive mental health; EWB – Emotional well-being; PWB – Psychological well-being; SWB – Social well-being; OS – Occupational stress; PFC – Problem focused coping; EFC – Emotion focused coping; SS – Social support; SD – Standard deviation

The confirmatory factor analysis (CFA) for the scale of MHC, WOC-R (problem-focused coping and social support), and OSI was carried out after applying squared multiple correlations to measure the construct reliability of indicator variables. All the items of emotion-focused coping were having very low factor loading. Hence, this construct was not considered for further analysis. Kaiser-Meyer-Olkin measure of sample adequacy for these scales came out at 0.808. Bartlett's test of Sphericity was also significant at the 1% level of significance P = 0.000 indicated that CFA could be applied to the data. The result of this CFA exhibited a good fit model (CFI = 0.976, RMSEA = 0.038 [90% confidence interval (CI) of 0.022–0.051]; SRMR = 0.042). All factors have standardized regression weights of >0.5. The model achieved convergent validity because the regression weights are statistically significant. Further, the correlation coefficient was also a minimum of 1 with standard deviations <0.05. Therefore, investigated factors obtained discriminant validity. The calculation of composite reliability (CR) and average variance extracted (AVE) values shows that CR reaches to the requirement [Table 3]. However, the AVE value of occupational stress and positive mental health scales is slightly low (<0.5). In such cases, AVE remains possible for acceptance at 0.4 or higher, provided that CR is above 0.6.[3435] Consequently, entire scales in the current study are appropriate for further structural equation model analysis.

Table 3

Model validity measures

	CR	AVE	MSV	MaxR (H)	OS	PFC	SS	PMH
OS	0.750	0.430	0.429	0.756	0.656||
PF	0.825	0.544	0.273	0.847	−0.041	0.738||
SS	0.782	0.548	0.273	0.811	0.030	0.523***	0.740||
PMH	0.824	0.484	0.429	0.827	−0.655***	0.110	−0.032	0.696||

||Square root of AVE. CR – Composite reliability; AVE – Average variance extracted; MSV – Maximum shared variance; MaxR (H) – Maximum reliability (H); OS – Occupational stress; PFC – Problem focused coping; EFC – Emotion focused coping; SS – Social support

The proposed model shown in Figure 1 demonstrated a good fit (CFI = 0.999; RMSEA = 0.045 [90% CI of 0.000–0.132]; SRMR = 0.011). Occupational stress possesses negative impact on positive mental health (B = −0.710, P < 0.001). As evidence, the findings supported the positive effect of problem-focused coping on positive mental health (B = 0.146, P < 0.001). On the contrary, social support adversely affected positive mental health (B = −0.094, P < 0.040). However, occupational stress was not associated with problem-focused coping (B = −0.096, P < 0.126) including social support (B = −0.007, P < 0.915). Further, problem-focused coping and social support have not acted as an intermediary link between positive mental health and occupational stress due to nonsignificant beta [Table 4].

Figure 1

The positive mental health model of train driver. The direct and indirect effects indicating unstandardized estimates for path analysis of work stress through problem-focused coping style and seeking social support on positive mental health among train drivers. Age, experience, education, living area, and level of income were adjusted in this model. *P < 0.05, **P < 0.01, ***P < 0.001

Table 4

Mediation effect of coping styles on positive mental health and occupational stress

Parameter	Estimate	Lower	Upper	P
OS→PFCxPFC→PMH	−0.026	−0.071	−0.002	0.079
OS→SSxSS→PMH	0.001	−0.025	0.033	0.862

OS – Occupational stress; PFC – Problem focused coping; SS – Social support; PMH – Positive mental health

Moreover, the moderation effect of problem-focused coping and social support variables on positive mental health tested in the presence of each other's mediating effect. At this step, the two interactions of two variables that are OS_x_PFC and OS_x_SS were included. The result revealed a good fit model (CFI = 0.999, RMSEA = 0.035 [% CI of 0.000–0.109], SRMR = 0.013) following every plausible measure deemed while checking problem-focused coping as moderator and social support as a mediator. The moderation effect is supported as a significant beta from independent variables and interaction [Table 5 and Figure 2]. However, there was no moderation effect due to nonsignificant beta from independent variables in case of social support as moderator and problem-focused coping as a mediator [Table 5], although the model was a good fit (CFI = 0.999, RMSEA = 0.027 [90% CI of 0.000–0.076], SRMR = 0.030).

Table 5

Moderation Effect of occupational stress and coping styles on positive mental health

	Estimate	SE	CR	P	Standardized estimate
PMH<---OS	−1.315	0.074	−17.829	0.000	−0.704
PMH<---PF	0.346	0.121	2.855	0.004	0.131
PMH<---SS	−0.298	0.135	−2.209	0.027	−0.101
PMH<---OS_x_SS	−0.087	0.048	−1.809	0.070	−0.066
PMH<---OS_x_PFC	−0.121	0.051	−2.393	0.017	−0.088

SE – Standard error; CR – Critical ratio; PMH – Positive mental health; OS – Occupational stress; SS – Social support; PFC – Problem-focused coping; PF – Problem focused coping

Figure 2

The interaction effect of problem coping styles on relationship of occupational stress and positive mental health

The unconstrained multigroup path model of three living areas demonstrated a good fit (CFI = 0.997; RMSEA = 0.068 [90% CI of 0.032–0.045]; SRMR = 0.031]. This model is compared through structural weights of different groups. Table 6 indicates that all models of three living area groups are the same as P value 0.302 is not significant. Similarly, the unconstrained multigroup path model of two-income level demonstrated a good fit (CFI = 0.994; RMSEA = 0.059 [90% CI of 0.000–0.118; SRMR = 0.004]. Table 6 also indicates that both models of low- and high-income groups were also the same as nonsignificant P value 0.847. Results were similar across all living area and income groups, with no statistically significant differences noted at path levels.

Table 6

Model comparison through structural weights of living area and income level

Model	DF	CMIN†	P
Living area	34	37.355	0.302
Income level	17	11.184	0.847

†Chi-square value. DF – Degrees of freedom; CMIN – Chi-square statistics

DISCUSSION

The present study revealed that train drivers were on elevated positive mental hygiene consistent for the three well-being dimensions emotional, psychological, and social well-being. The high-stress level among Indian train drivers is also confirmed, although there was a strong, significant, and inverse relationship of occupational stress with positive mental health. Problem-focused coping and seeking social support emerged as the main coping mechanisms in the present study. Indians settle a recompense on background delicacy and temperament reconciliation. They equalize their reactions by discarding limits in behavior and thinking or by integrating equal, apparently opposite purposes inextricably. The common spheres, for instance, an occupation, elicit specific standards, and morals than a private place like home. A critical situation enables individuals to differ from the norms of behavior or to disembark an extraordinary action. Personal-related individuals are trustworthy and preferred, whereas strangers are alienated, disbelieved, and abandoned.[36]

There was a significant effect of problem-focused coping on positive mental health that conforms to earlier studies.[3738] Very few research studies tested this relationship in Indian organizational settings.[39] As evidence, the negative effect of social support has found on positive mental health. There is a change in the urban nuclear Indian family support system, and the traditional role expectations are undergoing a transition.[40] However, Indian culture is assumed to be collectivist, with a majority of Indians being allocentric. There exists a normative pressure to extend social support. An allocentric individual is expected to give and receive more social support than idiocentrics. It is unlikely that all allocentric would receive greater social support than those who are likely to have a sense of psychological well-being.[41]

Work stress was neither positively nor negatively associated with problem-focused coping style. In this regard, a study revealed that Indian military pilots used emotion-focused strategies in addition to problem-focused strategies. However, these are utilized less frequently than problem-solving explained as being due to a possible cultural difference.[42] Similarly, occupational stress was not related to any direction of seeking social support coping style. A single study was found for the corroboration of this finding.[43] One of the critical explanations for this outcome could be that train drivers’ nature of job stress may not have the solutions or expertise in their society, friends, and other acquainted people.

A substantial degree of problem-focused coping mechanisms had been attributable to enhanced mental health suggests their ability to withstand and cope with stress while nourishing mental health. This coping style moderates the influence of stress on life satisfaction and internalize psychopathology symptoms[3744] and associated with fewer problems with coping at work, higher job satisfaction, and better mental health levels.[45] Thus, it was predictive of decreased perceived stress and increased perceived efficacy with positive well-being.[4647] Contrary to our results, the social support in Indian participation significantly moderated positive psychological strengths with subjective well-being[48] and fully mediated the relation of psychological well-being.[4950]

In the Indian sociocultural milieu, the workers in rural areas were facing more social-related problems in their profession than urban areas, with a positive association between the low income, low experience, living area, and level of job stress,[5152] although some research found that locality does not play a substantial role in work stress.[53] In a similar vein, the proposed model was the same in every living area and the income level. Further, it has found that individual with higher education, belonging to an economic class, with family income more than three times of the minimum wage and who lived in urban areas employed more problem-focused coping.[54] Studies have also demonstrated that those who engaged in adaptive coping styles while encountering strained situations have improved perceived overall health and improved life satisfaction compared to whosoever apply maladaptive coping mechanisms.[38] In contrast, some modest increase or decrease in the frequency of seeking social support was related to positive mental health for the current study investigation. Nevertheless, such derogations in no way affect meaningful change across pathways depicting the link between the stress of the job and positive mental health in light of the living area and income level.

Limitations

The limitation of this study is the known drawback of self-reported scales and relatively low variance explained by coping styles in work stress. It is possible that, due to a lack of control, so many other factors must have affected. Therefore, in future, the researcher should do more control and experimental type of research.

Implications

The importance of positive mental health in the organization will raise awareness to generate a sustained workforce conducive to the positive impact on safety performance. This will further lead to the formation of human resources policy and prevention of accidents accordingly to initiate relevant training and counseling interventions.

CONCLUSIONS

The greater use of problem focused coping reduces work stress and increases positive mental health. Many lapses that happened due to human error in the railway underscores the need for the prevention strategy. The positive mental health in terms of well-being plays an essential part in it, which is very relevant today in this pandemic.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.