Abstract
Purpose
This paper aims to study and measure the level of the psychological well-being, of the employees in IT/ITES organizations and to find out whether the psychological well-being (PWB), of the IT/ITES employees significantly varies with their socio-economic and demographic profiles.
Design/methodology/approach
Study was conducted among the employees in IT/ITES companies in Infopark, a cluster of companies, in Cochin. There are 30,000 employees estimated as working in different companies in Infopark. Considering the size of the population, the researcher targeted 1200 sample respondents (covering 4% of the population) and distributed 1400 questionnaires to IT/ITES employees of different companies in Infopark. The response rate was 78%, hence, the researcher could get back 1092 filled questionnaires. However, out of 1092, filled questionnaires, 24 questionnaires (2.20%) were found to be either incomplete or with mistakes and hence not in usable nature. These were eliminated from the final sample. The final sample for this study is (1092–24) thus taken as 1068 IT/ITES employees (3.56%) in Infopark, Kochi. psychological well-being (PWB) of the employees in IT/ITES organizations was measured using the PWB scale by Ryff (1989). Data analysis was done using parametric tests like, independent sample test and analysis of variance.
Findings
The current study tries to explain the variation in PWB, of IT/ITES employees with respect to their socio-economic and demographic profiles. Based on the independent sample t-test and one-way ANOVA test results relating to H1a (gender), H1b (age), H1c (work-experience) and H1d (employment level) the overall hypothesis H1: PWB exhibited by the IT/ITES employees significantly varies with their socio-economic and demographic profiles is rejected. Hence it is concluded that PWB among IT/ITES employees do not significantly differ with respect to their socio-economic and demographic profile.
Research limitations/implications
The study results may help the academia, trainers and researchers to identify new ways of improving PWB among employees. It will also help them to focus on training programmes, targeting toward the betterment of PWB. Policymakers' role is significant in promoting PWB among employees so as to ensure sustainable organizational performance.
Practical implications
The study will help managers to provide a conducive work place where employees are psychologically mature and carry positive attitude toward work, work environment and co-workers. Planned interventions are necessary to enhance team spirit, cooperation, cohesiveness and collaboration among employees.
Social implications
With the study findings new psychosocial interventions could be offered to the IT/ITES professionals in the form of training and personality development programmes. This will directly influence team effectiveness among employees.
Originality/value
A study on PWB has not yet been done among the Infopark employees. Thus, a study to assess the level of PWB carried out among IT/ITES professionals in Kochi is quite a new approach. A study of this nature is believed to help employers take measures for enhancing the PWB which will help to improve the team performance and thus the performance of the company as a whole.
Keywords
Citation
Korula, P.U. and Injodey, J.I. (2024), "Psychological well-being among IT/ITES employees: a socio-economic and demographic analysis", Rajagiri Management Journal, Vol. 18 No. 1, pp. 73-81. https://doi.org/10.1108/RAMJ-01-2023-0010
Publisher
:Emerald Publishing Limited
Copyright © 2023, Pramodh Uthup Korula and Joseph I. Injodey
License
Published in Rajagiri Management Journal. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
PWB is considered as the principal component of overall human well-being and is related to physical as well as mental health, of individual employees. People perceive themselves as happy when they subjectively believe that they are happy. Psychological well-being brings along positive attitude and helps to overcome negative attitudes. For instance, circumplex model of emotion, assesses PWB in terms of the hedonic or pleasantness feeling of individuals. Studies have reported the significant role of hedonic or pleasantness dimension in the individual's life. Depressed people tend to have negative emotions, pessimistic approaches, low self-esteem and lower level of motivation, reduced working capability, hypertension or alcoholism than people having positive emotions, optimistic approaches, high self-esteem, high morale, high productivity and happier life (Aryan and Kathuria, 2017).
Aryan and Kathuria (2017) argued that investment in PWB pays dividend both at the organizational and individual level. And hence to be treated as an asset. The organization will be benefitted by improved outcomes and employee productivity, enhanced loyalty, commitment from the work force, etc. and the resultant lower employee turnover. The employees will be benefitted because of longer, better and happier lives, higher level of satisfaction. They also reported that many studies and researches have empirically examined the role of PWB on employee performance and proved that there is significant positive relationship between level of PWB in workplace and business outcome for organizations. Hence they argued in their study that it is essential to develop interventions that can contribute to PWB. Positive PWB contributes to resilience, hope, optimism and efficiency of employees. Cropanzano and Wright (2000) conducted several researches in explaining the relationship between PWB and performance at work. It is reported that positive and happy people will have better physical and intellectual outcomes and behavior and they will be more resilient during hardships. Therefore, one can say, that the level of PWB of the employees also affect team efficiency.
PWB is a broad and complex terminology that depends on several factors and changes with time. It varies according to the context and is linked to the psychosocial factors and perceived happiness or state of mind by an individual. Therefore, it changes from person to person. Ryff and Keyes (1995) proposed the most popular components that define PWB; these include self-acceptance, environmental mastery, purpose in life, positive relations with others, personal growth and autonomy.
The literature review reveals that in spite of several studies conducted on team effectiveness, PWB and resilience, there is still a gap in literature that clearly brings out the relationship among the three factors. Studies have been conducted on team effectiveness and well-being or on team effectiveness and resilience. But, as mentioned before, studies that directly correlate the relationship among these three factors is not available. Specifically, studies have not been conducted to assess the influence of PWB and resilience on team effectiveness among IT/ITES employees in India.
Padma et al. (2015) reported that employees in IT industry are prone to develop a lot of health problems due to continuous physical and mental stress of their work. New work relationships, job insecurity, insecurity regarding future working conditions and rapid obsolescence of skills are causes of stress. The level of stress that IT and ITES employees face is comparatively higher than other employees. Mathieu et al. (2008) pointed out that considerable amount of researches are required to be carried out in the field of work teams.
Thus, a study to assess the level of PWB, is carried out among IT/ITES professionals in Kochi. A study of this nature is believed to help employers take measures for enhancing the PWB which will help to improve the team performance.
Literature review
The PWB theory was propounded by Ryff (1989, 2014; Ryff and Keyes, 1995). Ryff argued that happiness is a short term measure of well-being. According to him, in order to achieve sustainable well-being, we need to focus more on the sense of meaning in life rather than focusing on satisfaction and happiness. She advocates eudemonic approach to well-being rather than hedonic approach to well-being and proposed six dimensions of PWB such as self-acceptance, positive relations, personal growth, and purpose in life, autonomy and environmental mastery.
Vazquez et al. (2009) analyzed hedonic and eudaimonic approaches to PWB. It is found that well-being is significantly linked with psychological satisfaction and has important implications for physical health. Also studied that PWB has major influence on the prevention and in the recovery of physical conditions and diseases. The positive emotions help to lower stress, morbidity and mortality and might improve the health and quality of life. Bireda and Pillay (2017) examined the perceived parent-child communication and well-being among 809 adolescents of Ethiopia. Findings reveal that the female participants are communicated more to their parents as compared to males. The study exhibits the significant relationship between children's perception of communication with both parents and their subjective well-being. Also found open parent–child communication has significant role on adolescents' well-being. Anyanwu (2010) evaluated the relationship between parental relationship and the PWB. Research was made on 4000 southeastern Nigerian adolescents studying in senior secondary schools. Outcome of the research indicate that parental relationship with their children is a significant predictor of adolescents' PWB (personal, social and emotional). It was also revealed that adolescents had more emotional and social than personal problems. Bashir and Sufiyanzilli (2015) compared the levels of PWB 100 of employees working in public and private sector of Aligarh, India. As per the findings of the study, PWB of employees working in the public sector is high as compared to those working in the private sector. Public sector employees score high on all the sub dimensions of PWB except autonomy and self-acceptance.
Ryff and Singer (2003) in their study argued that “resilient individuals were generally capable to maintain their physical and psychological health and had the ability to recover more quickly from stressful events”. There was found to be positive relationships between PWB and resilience in a study conducted among middle and late adolescents (Sagone and De Caroli, 2014).Some of the other studies which have shown that there is significant positive correlation between resilience and subjective well-being are Khalid and Abdul (2014) and resilience, optimism and PWB by Souri and Hasanirad (2011).Tonkin et al. (2018) assessed how an organization can build up resilience among employees through ensuring their well-being. The authors tested the impact of well-being intervention on dimensions of individual resilience which are stress-coping ability of employees called as personal resilience and adaptive workplace behaviors employee resilience or employee resilience. The analysis indicated that both personal and employee resilience had direct positive relationship but levels of employee resilience were high in respondents compared to personal resilience. The study suggested some practical initiatives such as games which promote the improvement of well-being. The findings revealed that leaders of organizations can provide resources to employees, which do not need to be a financial cost to organizations.
Premchandran and Priyadarshi (2018) analyzed the subjective and PWB of IT/ITES professionals and concluded that empowering leadership is the antecedent of well-being. They have found that work-family enrichment partially mediates the relationship between empowering leadership and both subjective and PWB. Their study contributes to the existing literature on well-being, by introducing the concept of work family enrichment as a mediator variable.
Objectives of the study
The main aim of the present study is to,
To study and measure the level of the psychological well-being, of the employees in IT/ITES organizations.
To find out whether the PWB, of the IT/ITES employees significantly varies with their socio-economic and demographic profiles
Hypothesis
H1: PWB exhibited by the IT/ITES employees significantly varies with their socio-economic and demographic profiles
Research methodology
Study was conducted among the employees in IT/ITES companies in Infopark, a cluster of companies, in Cochin. There are 30,000 employees estimated as working in different companies in Infopark. Sample was selected using systematic random sampling method. To decide on the sample size Cochran's Sample size formula was used and found as 385 for 30,000 employees of Infopark. Hence a sample size of 1200 which is well above the number that was representative of the population is targeted and distributed 1400 questionnaires to IT/ITES employees of different companies in Infopark. The response rate was 78%, hence, the researcher could get back 1092 filled questionnaires. However, out of 1092, filled questionnaires, 24 questionnaires (2.20%) were found to be either incomplete or with mistakes and hence not in usable nature. These were eliminated from the final sample. The final sample for this study is (1092–24) thus taken as 1068 IT/ITES employees (3.56%) in Infopark, Kochi.
PWB of the employees in IT/ITES organizations was measured using the PWB scale by Ryff (1989). Data analysis was done using parametric tests like, independent sample test and analysis of variance.
Results and discussion
The total sample for the study consisted of 1068 respondents who were the employees of IT/ITES firms. Their demographic and socio-economic profile was inquired into. Their age, gender, income, level of employment and their work experience were inquired into. The age category of respondents was divided into three – “below 25 years”, “25–40 years” and “above 40 years”. The results show that among the total 511 males, 183 are below 25 years and 173 are between 25 and 40 years. As regards the 557 female respondents, 193 are below 25 years, while 183 are above 40 years.
Reliability analysis
Cronbach's Alpha coefficient was computed to examine the scale reliability to understand how well all the six indicators together measure the PWB of the respondents (Table 1). For the six indicators of PWB, the Cronbach's Alpha values are ranging from 0.801 to 902, which is above the recommended value of 0.80 (Cortina, 1993), proving that the scale is reliable.
Descriptive statistics
Based on the mean scores of the indicators for the six components of PWB, a component-wise mean score was computed, which is then used to arrive at an overall level of PWB (Table 2). The score ranged from one (minimum level) to five (maximum level). The following table presents the results.
Overall psychological well-being: socio-economic and demographic analysis
The responses on the various indicators related to the six dimensions of PWB were composed into a mean score within the range of 1.00 (minimum) to 5.00 (maximum) to arrive at an overall well-being score. The overall PWB was then decomposed for various demographic factors – age, gender, experience at work and employment level. Shaprio-Wilk test was run to test for normality of data. Independent sample t-test and one –way ANOVA was run to identify whether there was statistically significant difference in levels of PWB based on various demographic factors. The following hypothesis was tested,
PWB exhibited by the IT/ITES employees significantly varies with their socio-economic and demographic profiles
The hypothesis was separately tested for gender (H1a), age (H1b), work-experience (H1c) and level of employment of respondents (H1d).
Gender and psychological well-being
Gender-wise mean scores (Table 3) of well-being are similar for males (3.498 ± 0.761) and females (3.488 ± 0.801). Shapiro–Wilk test results (p value > 0.05) show that the data followed normal distribution. T-test results (Table 4) show that there exist no statistically significantly difference in levels of PWB between males and females (T = 0.902; p value > 0.05).
Thus, the study rejects the hypothesis.
PWB exhibited by the IT/ITES employees significantly varies with their gender.
Age and psychological well-being
Age-wise mean scores (Table 5) of well-being are found to be above moderate level for less than 25 years (3.501 ± 0.179), between 25 and 40 years (3.482 ± 0.172) and for above 40 years (3.496 ± 0.186). Shapiro–Wilk test results (p value > 0.05) show that the data followed normal distribution.
One-way ANOVA results (Table 6) show that there exist no statistically significant variance in the levels of PWB among the three age categories (F = 1.242 (df = 02, 1065); p value > 0.05). Thus, the study rejects the hypothesis.
PWB exhibited by the IT/ITES employees significantly varies with their age category.
Experience and psychological well-being
Work experience-wise mean scores of well-being (Table 7) are found to be the following for the three categories of respondents: less than 05 years (3.491 ± 0.179), between 05 and 15 years (3.500 ± 0.176) and for above 15 years (3.488 ± 0.184).
Shapiro–Wilk test results (p value > 0.05) show that the data followed normal distribution. One-way ANOVA results (Table 8) show that there exist no statistically significant variance in the levels of PWB among the three categories based on experience (F = 0.461 (df = 02, 1065); p value > 0.05). Thus, the study rejects the hypothesis.
PWB exhibited by the IT/ITES employees significantly varies with their experience.
Employment and psychological well-being
Mean scores of well-being based on the level of employment of respondents are found to be the following for the three categories: lower level employees (3.490 ± 0.180), middle level employees (3.493 ± 0.179) and higher level employees (3.511 ± 0.183). See Table 9 for details.
Shapiro–Wilk test results (p value > 0.05) show that the data followed normal distribution. One-way ANOVA results (Table 10) show that there exist no statistically significant variance in the levels of PWB among the three categories based on level of employment (F (df = 02, 1065) = 0.625; p value > 0.05). Thus, the study rejects the hypothesis.
PWB exhibited by the IT/ITES employees significantly varies with their employment level.
Conclusion
The current study tries to explain the variation in PWB, of IT/ITES employees with respect to their socio-economic and demographic profiles. Based on the independent sample T-test and one-way ANOVA test results relating to H1a (gender), H1b (age), H1c (work-experience) and H1d (employment level) the overall hypothesis H1: PWB exhibited by the IT/ITES employees significantly varies with their socio-economic and demographic profiles is rejected. Hence it is concluded that PWB among IT/ITES employees do not significantly differ with respect to their socio-economic and demographic profile. The reason for this finding may be attributed to the fact that irrespective of demographic profile of the IT/ITES employees, they all experience the same level of work pressure as well as deadlines for completion of their work. The study results may help the academia, trainers and researchers to identify new ways of improving PWB among employees. It will also help them to focus on training programs, targeting toward the betterment of PWB. Policymakers' role is significant in promoting PWB among employees so as to ensure sustainable organizational performance. The study will help managers to provide a conducive work place where employees are psychologically mature and carry positive attitude toward work, work environment and co-workers. Planned interventions are necessary to enhance team spirit, cooperation, cohesiveness and collaboration among employees. With the study findings new psychosocial interventions could be offered to the IT/ITES professionals in the form of training and personality development programs. This will directly influence team effectiveness among employees. The study will further help in adding to the existing body of knowledge and address the gaps identified in literature review.
Scope for further research
The socio economic and demographic profiling of the respondents may be expanded by adding more features to age, gender, employment level and work experience and further study can be done to identify if there are any impact on PWB. The present study may be used in different comparative studies of PWB done in sectors other than IT and ITES also.
Reliability statistics
| Indicators | Cronbach's alpha | No. of items |
|---|---|---|
| Psychological well-being | ||
| Autonomy | 0.825 | 07 |
| Environmental mastery | 0.889 | 07 |
| Personal growth | 0.902 | 07 |
| Positive relations with others | 0.801 | 07 |
| Purpose in life | 0.836 | 07 |
| Self-acceptance | 0.862 | 07 |
Source(s): SPSS Results
Psychological well-being: descriptives
| Components | Mean | S. D | Skewness | Kurtosis |
|---|---|---|---|---|
| Autonomy | 2.998 | 0.524 | 0.112 | −0.192 |
| Environmental mastery | 3.477 | 0.426 | 0.010 | −0.204 |
| Positive relations with others | 3.509 | 0.433 | 0.040 | −0.219 |
| Purpose in life | 4.004 | 0.301 | 0.063 | 0.411 |
| Personal growth | 3.994 | 0.305 | 0.011 | −0.284 |
| Self-acceptance | 2.977 | 0.560 | −0.051 | −0.346 |
| Psychological well-being | 3.493 | 0.179 | 0.105 | −0.094 |
Source(s): SPSS Results
Gender-wise psychological well-being
| Gender | Mean | S. D | Shapiro–Wilk | |
|---|---|---|---|---|
| Static | Sig | |||
| Male | 3.498 | 0.761 | 0.996 | 0.166 |
| Female | 3.488 | 0.801 | 0.983 | 0.106 |
Source(s): SPSS Results
Gender-wise difference in psychological well-being: T-test
| F-static | Sig | T-static | Sig | |
|---|---|---|---|---|
| Equal Variances Assumed | 0.460 | 0.498 | 0.902 | 0.367 |
Source(s): SPSS Results
Age-wise psychological well-being
| Age | Mean | S. D | Shapiro–Wilk | |
|---|---|---|---|---|
| Static | Sig | |||
| <25 yrs | 3.501 | 0.179 | 0.994 | 0.110 |
| 25–40 yrs | 3.482 | 0.172 | 0.993 | 0.089 |
| >40 yrs | 3.496 | 0.186 | 0.995 | 0.290 |
Source(s): SPSS Results
Age-wise variance in psychological well-being: one-way ANOVA
| Sum of squares | df | Mean square | F | Sig | |
|---|---|---|---|---|---|
| Between groups | 0.080 | 02 | 0.040 | 1.242 | 0.289 |
| Within groups | 34.217 | 1065 | 0.032 | ||
| Total | 34.297 | 1067 |
Source(s): SPSS Results
Experience-wise psychological well-being
| Experience | Mean | S. D | Shapiro–wilk | |
|---|---|---|---|---|
| Static | Sig | |||
| <05 yrs | 3.491 | 0.179 | 0.993 | 0.129 |
| 05–15 yrs | 3.500 | 0.176 | 0.995 | 0.224 |
| >15 yrs | 3.488 | 0.184 | 0.990 | 0.140 |
Source(s): SPSS Results
Experience-wise variance in psychological well-being: one-way ANOVA
| Sum of squares | df | Mean square | F | Sig | |
|---|---|---|---|---|---|
| Between groups | 0.030 | 02 | 0.015 | 0.461 | 0.631 |
| Within groups | 34.267 | 1065 | 0.032 | ||
| Total | 34.297 | 1067 |
Source(s): SPSS Results
Employment-wise psychological well-being
| Employment level | Mean | S. D | Shapiro–wilk | |
|---|---|---|---|---|
| Static | Sig | |||
| Lower level | 3.490 | 0.180 | 0.995 | 0.146 |
| Middle level | 3.493 | 0.179 | 0.993 | 0.072 |
| Higher level | 3.511 | 0.183 | 0.986 | 0.345 |
Source(s): SPSS Results
Employment-wise variance in psychological well-being: one-way ANOVA
| Sum of squares | df | Mean square | F | Sig | |
|---|---|---|---|---|---|
| Between groups | 0.040 | 02 | 0.020 | 0.625 | 0.535 |
| Within groups | 34.257 | 1065 | 0.032 | ||
| Total | 34.297 | 1067 |
Source(s): SPSS Results
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