Work-life balance and psychological distress: A structural equation modeling approach

2.1 Work-family conflict, family-work conflict & psychological distress

[18] defined work-life balance as “juggling competing demands was tiring if not stressful and brings lower productivity, sickness, and absenteeism, so work/life balance was an issue for all employees and all organizations.” There are many factors which contribute to the work-life balance of an individual. The current study tried to explore those factors and its relationship with psychological distress.

Work-family conflict or work influence on family is a type of inter-role conflict that negatively affects both the spheres work and family [19–22]. Argued that work-family conflict occurs when an individual gives more time to work and not able to give time to his/her family. Therefore it contributes to stress because work and family are contrary to one another; fulfilling one role may create conflict for another role or demand. The conflicts between two are inevitable because both have different demands, priorities, goals, norms and expectations [23, 24]. Work-family conflict is not always considered either work or life; both the demands coexist in harmony, leading to conflict [25, 26]. Opined that an individual needs to balance work and life because as the work starts interfering in family life, it generates stress and reduces productivity. It also leads to negative consequences like negative spillover, interruption and high imbalance between efforts and rewards [27]. Work-family conflict is not only harm the employees but also harmful for employers. Work-family conflict is characterized by bi-dimensional effect; one work affecting family and second family affecting work [28, 29]. To understand the work-family conflict, it is imperative to understand family-work conflict [19]. Work-family conflict and family-work conflict are different in nature and lead to different treatment to be given [30]. Both have different antecedents and attitude in terms of work and non-work activities [31]. Therefore, analyzing work-family conflict and family-work conflict need close observation of various aspects of one’s life like work and non-work activities performed by an individual, satisfaction and psychological involvement in those activities [32]. Managing work-life conflict will lead to reduced stress and foster employee well-being [33].

Work-family conflict is having a high association with psychological strain [34], poor physical well-being [35], higher fatigue [36] and depression and fretfulness [37]. Psychological stress can be defined as, “an umbrella term that encompasses stress, burnout, depression, anxiety and other related mental health problems” [38]. At the workplace, psychological distress originated from unhappiness, depression, anxiety, workload, the primary dimension [39], and [40] reported as mental illness generation from occupational stress [41]. Found that psychological stress is a result of work-family conflict, job pressure work experiences among Australia’s construction professionals. In past studies, work-family conflict and family-work conflict have been considered as predictors of burnout and stress [35, 43]. Previous studies have mentioned that work-family conflict is having a strong association with psychological distress than family-work conflict [44, 45]. To confirm the past research revelations among the banking sector employees in the Indian context, researchers hypothesized that;

2.2 Job satisfaction, family satisfaction, life satisfaction & psychological distress

Job satisfaction is described as one of the most studied topics as most of the literature on organiza-tional and industrial psychology, social psychology, organizational behaviour and human resource management includes this concept [46, 47]. Job satisfaction is defined as “a pleasurable emotional state that results from an individual appraisal of one’s job” [48]. Family Satisfaction can be defined as, “the extent to which an individual is satisfied with his or her family life or situation” [49]. Life satisfaction can be understood as a cognitive appraisal of the overall degree of satisfaction an individual has with his/her life [50]. Life satisfaction leads to many advantages, like a person feel good about his/her life. It also affects the well-being of an individual. Life-satisfaction leads to happy and healthy life, and such individuals treat others better [51]. It was pointed out by [52], “When people are happier, they tend to be more open-minded and creative in their thinking. In contrast, people who are unhappy, stressed, or dissatisfied tend to exhibit ‘tunnel vision’ and rigid thinking” [p. 32]. Work itself can be the source of stress or lead to psychological distress, “conditions that place excessive/unusual demands on a person and are capable of engendering psychological discomfort [that is, stress, physiological pathology, and/or social disability]” [53]. Majority of the past research focuses on the relationship between work-family conflict and family-work conflict and job satisfaction, family satisfaction and life satisfaction. For example [2] conducted a study on sales people. It was found that high family-work conflict lead to lower job satisfaction [54]. Conducted a study on Malaysian employees of diverse industries found that family-work conflict decreased job satisfaction while the work-family conflict was having no relation with job satisfaction [55]. Conducted a study on frontline employees of hotel industry in the US. It was revealed that work-family conflict is having a negative impact on job satisfaction while the work-family conflict was having positive impact on job satisfaction [56]. Found that there is negative relationship between work-family conflict and life satisfaction, whereas [57], found that there is negative association between family-work conflict and life satisfaction as well [58]. Also found negative relationship between family-work conflict and life satisfaction. Very few studies directly checked the relationship of job satisfaction, family satisfaction and life satisfaction with psychological distress [59]. Found that high psychological distress prevalent among Chinese nurses and job satisfaction was affected by psychological distress felt by nurses [60]. Found that highly satisfied teachers have low psychological distress. Relationship between stress and life satisfaction have been explored in past studies [19, 61]. Proposed that role stressors lead to fatigue and it affects the life satisfaction of an individual. There is a negative association between stress and life satisfaction [62, 63]. The researchers found that none of the studies have tried to explain holistically that there is an association between job satisfaction, family satisfaction and life satisfaction with psychological distress. To address this lacuna in the previous studies researchers hypnotized that;

2.3 Work overload, work autonomy & psychological distress

“Work overload is described as more number of assignments or work given to the employees as compare to his/her capability and resources”. It is also characterized by strict deadlines and huge workload [64, 65]. The critical outcome of work overload is stress [66, 67]. found that work overload and psychological distress are positively correlated whereas [68], found that work overload and psychological distress are negatively related [69]. Found an insignificant association between work overload and psychological distress, whereas [70] found a significant relationship between work overload and psychological distress [71]. Found that work overload leads to psychological distress and also affected the poor concentration, poor decision making and mental block [68]. Found a significant positive relationship between work overload and psychological distress among employees of the banking sector in Pakistan. High performers perceived workload also lead to stress and exhaustion [72].

Work autonomy is defined as, “designing jobs in ways which give employees wide scope to enact work” [73]. [74] explained autonomy as a part job characteristics model. It replicates the degree to which job permits self-determination and freedom to take decisions at work. Autonomy enables flexibility in terms of arranging individual work [75]. The excessive high amount of autonomy can lead to strain [19]. Work autonomy gives control over the task carried out by an individual [76] which lead to stress. [77] explored that the mismatch between demand placed on individuals and the ability to control those demands is crucial to psychological distress. As higher, the control lowers the psychological distress. [78] explored that autonomy was having a reducing effect on role stress. [79] discovered that work autonomy was crucial contextual factor in decreasing the effect of job demand on psychological distress. In the Indian context, the relationship between work overload, work autonomy and psychological distress is remaining unexplored. Therefore, the current study proposes the following hypotheses:

3.1 Measures

Work-Family Conflict and Family-Work Conflict were measured using [2] scales. Both the work-family conflict and family-work conflict scales are composed of five items each. Work role overload was measured using a five-item subscale of the Organizational Role Stress Scale developed by [80]. Work autonomy and job satisfaction were measured using [81] Job Diagnostic Survey of three and five items, respectively. Family satisfaction was measured using a modified version of the 10 item general family satisfaction scale developed by [82]. Because the scale was developed as a measure of satisfaction with one’s family of origin, items were reworded to measure satisfaction with one’s family of procreation. Life satisfaction was measured using a five-item satisfaction with life scale developed by [83].

To measure the psychological distress, we re-viewed the extant literature and found that Center for Epidemiological Studies’ Depression Scale [CES-D] is not only used for depression, but it can also be used for the psychological distress [84, 85]. in their seminal work emphasized that the CES-D scale is not solely used to measure depression but is also the best measure of psychological distress. Hence, psychological distress was measured using the CES-D scale developed by the National Institute on Mental Health [86].

4.1 Reliability & validity

Reliability was assessed using Cronbach’s alpha. Table 1 depicts that all the variables under study demonstrate values above 0.7, and hence it is admissible [87]. We examined the convergent and discriminant validity. Bootstrapping was done to estimate the outer loadings and level of significance, and it was found that all the outer loadings were more than 0.5 [except WA1,2, PD1,2,4, WF1, LS4,5, FS3,4,5,7,8] and significant at p < 0.001 [Refer Fig. 1]. As per [88], AVE’s values should be more than 0.5, which explains that beyond 50 per cent of the variance of respective constructs compared with the errors explained. Discriminant validity can be checked using the Forner-Larcker Criterion [89]. According to the Forner-Larcker measure, ‘the AVE of each construct should be higher than the construct’s highest squared correlation with any other latent construct’, and in cross-loadings’ represented in Table 1. Based on the diagonal elements [^a], discriminant validity is established.

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Fig. 1

Result of first run through SMARTPLS3.1.

To check the issue of multicollinearity, the variance inflation factor [VIF] among constructs was examined. The outer VIF values show the collinearity among the items in constructs, and inner VIF shows the collinearity among the latent variable [89] suggested that the value of VIF should be less than five. Table 2 shows the collinearity statistics of all the constructs [inner VIF] and all the values of VIF are less than five. Similarly, for the outer VIF refer to Table 2. This implies that there are no collinearity problems existing among the constructs.

In the PLS-SEM context, the common method bias (CMB) occurs because of the measurement model’s errors rather than the cause and effect in the structural model [90]. As the data was collected from a single instrument, Harman’s single factor test was conducted to check that data was free from common bias, and single factor was accounted for 14.48 per cent of the variance. Hence, the data was free from common method bias [91]. Further, nonresponse bias is found as no difference was seen between the early and late respondents in the survey [92].

4.4 Structural model

After checking the measurement model’s compatibility, the structural model [refer to Fig. 2] is analyzed to verify the proposed hypothesis and predict the model. In PLS-SEM, the model can be predicted by estimating R² and Q². R² is accurately predicting the variance explained by the construct, and Q² proposes predictive relevance by using the sample reusing method where part of the data matrix is being omitted and results are used to predict the omitted part [93]. Stated that the higher the R² [ranging from 0 to 1], the higher the predictive accuracy. The R² of the exogenous variables psychological distress was 0.267, which was higher than 10 per cent, as recommended by [94] and considered to be good, as suggested by [95]. Hence, it signifies a robust explanatory power of the model, which infers that work-family conflict, family-work conflict, work overload, family satisfaction and life satisfaction contribute 26.7 per cent of the total variance in psychological distress. The significance of the model fit was checked using SRMR [standardized root mean square residual] values. R-square of the model is 0.265, so it can be said that 26 per cent of the variation in psychological distress among banking sector employees can be explained through work-family conflict, family-work conflict, job satisfaction, life satisfaction, family satisfaction, work overload, work autonomy [Table 3]. SRMR is a badness-of-fit index [larger values signal worse fit], and it ranges from 0.0 to 1.0.value below. Models obtaining values less than 0.05 is said to be a very good fit [96, 97]. However, a model with SRMR value less than 0.08 is generally considered as a good fit model. [98]. SRMR value for the current model under study is 0.065, which is below 0.8 threshold limit and hence it can be said that model is significant and good fit.

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Fig. 2

Results of second run from SMARTPLS3.1.

To verify the predictive orientation of the model, the Stone-Geisser’s Q² is used [95, 99]. The assessment of Q² proposes predictive relevance by using sample reusing method where part of the data matrix is being omitted, and results are used to predict the omitted part. Hence, this blindfolding technique assesses the model’s predictive accuracy. The higher value of Q² implies less deviation in estimated and original values. Hence, Q² should be more significant than 0 [refer to Table 3] [89]. Recommended that the values of Q², that is, the predictive indices 0.02, 0.15, and 0.35, are regarded as small, medium and large effects, respectively. Here, Q² value of the family satisfaction was 0.05, and work overload was 0.024; it infers that family satisfaction and work overload has a low effect in predicting variance in psychological distress. Whereas, the other variables were having no effect [Table 3].

F² is calculated to estimate the effect size [100]. Suggested that the values of f² as 0.02, 0.15 and 0.35 are considered to have small, medium and large effects, respectively. Table 3 reflects the f² effect size. Family-work conflict and work overload were having 0.027 and 0.048, i.e. small effect size. Whereas, family satisfaction was having 0.157 medium effect size.

To verify the postulated hypothesis and check the relationship among the constructs, the path coefficients are calculated by using the bootstrapping, t values and P values. From Table 4, it is revealed that the bootstrapping results of resampling technique [5,000 subsamples] examine the influence of work-family conflict, family-work conflict, work overload, family satisfaction and life satisfaction on psychological distress. Table 4 depicts the path coefficients, t values and P values of the proposed hypothesis. It can be seen from Fig. 3 and Table 4 that out of 5 variables, only 3 variables have t values greater than 1.96, namely family-work conflict, family satisfaction and work overload are statistically significant and positively correlated with dependent variable psychological distress. The Beta values of path coefficient help to find out the type of relation and magnitude of the relationship of independent variable with the dependent variable. Family satisfaction [–0.356] has the highest value of coefficient among all the variables followed by work overload [0.228], and family-work conflict [0.124].

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Fig. 3

Bootstrapping results obtained through SMARTPLS3.1.