Level and Relationships of Life Satisfaction with Cognitive Flexibility and Resilience in IT Professionals.

Introduction: Information Technology (IT) professionals commonly encounter occupation-related issues that adversely affect psychological health and well-being. Aim and Objective: To study the level and relationships of life satisfaction with cognitive flexibility and resilience in IT professionals. Materials and
Methods: In this cross-sectional study, 457 IT professionals were assessed with Sociodemographic proforma, Cognitive Flexibility Scale (CFS), Cognitive Resilience Scale (CRS), and Satisfaction with Life Scale (SWLS). Statistical Analysis Used: Descriptive statistics, Student's t-test, ANOVA, and linear regression analysis.
Results: The mean score on CRS was high (4.5), whereas on CFS was low (49.36). The mean score on SWLS was also low (17.36) particularly with widowed and disrupted family status, positively linked to the scoring of CFS & CRS, and negatively linked to hours of work. Conclusions: Among Indian IT professionals, cognitive flexibility and life satisfaction are low and influenced by family. Life satisfaction is proportionately linked to cognitive flexibility and resilience. Copyright:

INTRODUCTION

Information technology professionals often encounter emotional dissonance, work exhaustion[123], professional and role stress,[45] job burnout,[6] and multiple issues related to jobs.[7] Among Indian IT professionals stress is mounted by the constant change in technology, client interaction, fear of obsolescence, family support, long working hours, work overload, and so on.[89] High stress is often accompanied by different psychological issues such as depression, anxiety, and insomnia,[10111213] and it is not common to see the Indian media reporting suicide. It appears that psychological function may also be affected by issues that arise out of their occupation. Life satisfaction may significantly depend upon employment and professional satisfaction,[141516] though other factors may also play a role among Asians such as age, marital status, the standard of living, and so on.[1718] Life satisfaction is “a global assessment of a person's quality of life according to his chosen criteria”.[19] Life satisfaction is an integral part of subjective well being; hence impairment may be linked to early morbidity/mortality,[20] and impaired job performance.[21]

Cognitive flexibility in IT professionals may also be influenced by their occupation-related issues,[22] though there is paucity of studies addressing this variable. The reported factors that may impair it are elevated cognitive dissonance[23] and job burnout.[2425] Cognitive flexibility is the ability to adaptcognitive processing strategies to face new and unexpected conditions in the environment.[26] Those with a higher level of flexibility would be flexible enough to deal with changes in the environment and hence able to adopt a new situation.[26] Impaired flexibility may impair learning, resilience to stress, reduced creativity, and poorer quality of life,[27] and ultimately impaired performance.[28]

Cognitive resilience may also be impaired,[29] though we could not trace any study examining the cognitive resilience among IT professionals. It is the capacity to overcome the negative effects of setbacks and associated stress on cognitive function or performance.[30] Though there are different approaches to understanding resilience, here it is used as a positive personality trait that promotes adaptation[3132] and individual attributes that can facilitate the ability to cope when confronted with stressful life events.[33] High resilience has been associated with well-being,[34] life satisfaction and engagement,[353637] tolerance of negative affect, and strengthening effects of stress.[32] Cognitive resilience among the IT professionals may be impaired by job burnout,[38] job stress,[39] and prolonged workload.[40]

Indian IT industry is growing exponentially; it contributes to 7.7% of the GDP of India and the highest export relative to its share in Gross value added.[41] IT personnels represent a dynamic workforce in a new and high-growth industry of the future, and an important component of the workforce. They can aid companies and government in leveraging IT to improve efficiency and compete electively in the global markets. However, less attention has been devoted to examining the different aspects of psychological health that may be linked to their profession. Thus, this study was conducted to know the level and relationships of life satisfaction with cognitive flexibility and resilience in IT professionals. We hypothesized that life satisfaction would positively link to cognitive flexibility and resilience.

MATERIALS AND METHODS

This cross-sectional study was conducted among IT professionals working in different IT companies in the Mysore and Bengaluru area of Karnataka, India, after obtaining approval from the Institutional Ethical Committee. Assuming a moderate correlation, 95% confidence level, 5% of margin of error, the estimated size of population was 385.[42] Snowball sampling was used to recruit the participants. For this study, an online google form was created to gather information, and a link was sent to the WhatsApp group of IT professionals, with a consent form attached to it that does not contain the personal identity of responders. After acceptance, the participant can respond to questions. It also mentions that participants have the right not to participate. The form consisted of four parts; the initial part was demographic and professional details, the second third, and fourth part were self-rating cognitive flexibility scale (CFS), cognitive resilience scale (CRS), and Satisfaction with Life Scale (SWLS), correspondingly. The study started on 03/05/2020 and ended on 24/08/2020. Inclusion criteria of the study were aged 18 or above, of any gender, able to read English, and working as IT professionals for a minimum of 1 year after obtaining a degree or diploma. Those with incomplete responses and a history of chronic mental illness were excluded from the study.

A total of 518 responses were received by the stipulated time, and a total of 457 responses were found to have met eligibility criteria and were included. The tools of assessment were –

Sociodemographic proforma

The proforma consisted of Age, Gender, Occupational designation, Religion, Marital Status, Family type, Socioeconomic status, any substance use, typical working hours, participation in any leisure activity, and history of chronic physical or mental illness. Socioeconomic status was assessed using Standard of Living Index (SLI) scale.[43]

Cognitive flexibility scale (CFS)

Martin and Rubin developed these 12 items, self-report, 6point Likert scale (strongly disagree to strongly agree) to measure cognitive flexibility in 1995.[44] The items consist of statements about belief and feeling of own behavior, which respondents needed to best describe them. A higher score indicates more cognitive flexibility. The scale has high internal consistency (α = 0.76–0.77), concurrent and construct validity, and test–retest reliability (r = 0.83) over 2 weeks.[44] This scale has been used in the Indian population.[45]

Cognitive resilience scale (CRS)

Smith developed these 10 items, self-report, 5-point Likert scale (disagree = 1 to strongly agree = 5) to measure cognitive resilience in 2015.[46] Response bias is taken care of by reverse scoring of items 2, 4, 5, 6, and 8. The score is calculated by adding up all 10 items divided by 10. A score between 1.00 and 2.99 indicates low, 3.00–4.30 normal, and 4.32–5.00 to be high. A higher score indicates more resilience.

On reliability measure, the scale has Cronbach's Alpha value of 0.89 good validity score. This scale has been used in the Indian population.[45]

Satisfaction with life scale (SWLS)

Diener et al.[47] developed these 5 items, self-report, Likert scale (1 = strongly disagree to 7 = strongly agree), with possible scale range 5–35. A score below 20 indicates low satisfaction, whereas a higher score indicates more satisfaction. The reliability score ranged from 0.79 to 0.89 and had a good validity score. The scale has been used in the Indian population.[45]

Statistical Analysis was done using Statistical Package for the Social Sciences 22nd version (SPSS vs 22). Descriptive statistics was used to analyze sociodemographic and clinical features. Independent t-test was used to analyze relationships of gender and leisure activity with the score on CFS, CRS, and SWLS. A simple linear regression analysis was carried out to know the relationships of working hours with the score on CFS and CRS (working hours as predictor and score on CFS and CRS as dependent variable). ANOVA test was conducted to examine the relationships of sociodemographic variables with score on CRS, CRS, and SWLS. A multiple regression analysis was also carried out to know the relationships of (predictor variables) age, working hours, CFS score, and CRS score with the score on SWLS (dependent variable). The significance of the statistical test was set to P = 0.05.

RESULTS

The majority were males working in Business Process Outsourcing, married, belonged to a nuclear family, of middle socioeconomic status, and did not report substance use [Table 1a].

Table 1a

Sociodemographic and clinical features

Variables		n	%
Gender	Male	257	56.2
	Female	200	43.8
Designation	Business Process Outsourcing	299	65.4
	Project head	106	23.2
	Organization head	52	11.4
Education	PUC/12th/Diploma	29	6.3
	Degree	190	41.6
	Master’s degree	229	50.1
	Other	9	2.0
Religion	Hindu	246	53.8
	Muslim	111	24.3
	Christian	88	19.3
	Other	12	2.6
Marital status	Single	181	39.6
	Married	258	56.5
	Divorced	12	2.6
	Separated	6	1.3
Family type	Nuclear	295	64.6
	Joint	143	31.3
	Others	19	4.2
Socioeconomic status	Low	29	6.3
	Middle	380	83.2
	High	48	10.5
Substance use	None	307	67.2
	Cigarette	68	14.9
	Alcohol	22	4.8
	Other	20	4.4
Leisure activity	No	196	42.9
	Yes	261	57.1

The mean of age and working hours were 32.4 (±5.9) years, and 9.39 (±2.0) hours, respectively. The mean score on the CFS, CRS, and SWLS was 49.36 (±10.5), 4.50 (±0.3), and 17.36 (±3.5) respectively [Table 1b].

Table 1b

Sociodemographic and clinical features

	Minimum	Maximum	Mean	Std. Deviation
Age	10.00	55.00	32.48	5.9
Working hours	4	4.50	3.00	0.3
CFS Score	1.60	72.00	49.36	10.5
CRS Score	1.60	4.50	3.00	0.3
SWLS Score	5.00	25.00	17.36	3.5

CFS=Cognitive Flexibility Scale, CRS=Cognitive Resilience Scale, SWLS=Satisfaction with Life Scale

Independent t-test was done to examine the relationships of life satisfaction, cognitive flexibility, and resilience with gender and leisure activity. No statistically significant relationship was observed except for life satisfaction and leisure activity (t = -3.126, df = 455, P = 0.002) with Cohen d of -.29 (Small effect) [Table 2a].

Table 2a

Relationships of life satisfaction, cognitive flexibility, and resilience with gender and Leisure activity

	Variables	N	Mean	Std. Deviation	Std. Error Mean	t	df	P	95% Confidence Interval of the Difference
									Upper	lower
CFS Score	Male	257	49.57	10.60	0.66	0.498	455	0.618	-1.45	2.44
	Female	200	49.08	10.41	0.73
CRS Score	Male	257	3.0257	0.36737	0.02292	1.580	455	0.115	-0.01	0.118
	Female	200	2.9735	0.32693	0.02312
SWLS Score	Male	257	17.43	3.67	0.22	0.436	455	0.663	-0.51	0.80
	Female	200	17.28	3.44	0.24
CFS Score	Without LA	196	49.53	10.24	0.73	0.303	455	0.762	-1.65	2.25
	With LA	261	49.23	10.73	0.66
CRS Score	Without LA	196	3.0255	0.38412	0.02744	1.197	455	0.232	-0.02	0.10
	With LA	261	2.9858	0.32331	0.02001
SWLS Score	Without LA	196	16.77	3.17	0.22	-3.126	455	0.002	-1.70	-0.38
	With LA	261	17.81	3.79	0.23

LA=Leisure activity, CFS=Cognitive Flexibility Scale, CRS=Cognitive Resilience Scale, SWLS=Satisfaction with Life Scale

To know the relationship of cognitive flexibility with sociodemographic variables, ANOVA test was done. It has a statistically significant relationship with Religion (df = 3; F = 3.66; P = 0.012; η2 = 0.024 (small), Marital status (df = 3; F = 3.37; P = .022; η2 = .032 (small), Family status (df = 2; F = 7.46; P = .001; η2 = .032 (small), Socioeconomic status (df = 2; F = 3.77; P = .024; η2 = .016 (small), and Substance use (df = 4; F = 5.77; P = .001; η2 = .049 (small) [Table 2b].

Table 2b

Relationships of cognitive flexibility with sociodemographic variables

	Sum of Squares	df	Mean Square	F	Sig.	η2
CFS Score * Designation	383.19	2	191.59	1.73	0.177	0.008
CFS Score * Education	438.24	3	146.08	1.32	0.266	0.009
CFS Score * Religion	1194.26	3	398.08	3.66	0.012	0.024
CFS Score * Marital status	1103.27	3	367.75	3.37	0.018	0.022
CFS Score * Family status	1605.45	2	802.72	7.46	0.001	0.032
CFS Score * SES	825.63	2	412.81	3.77	0.024	0.016
CFS Score * Substance use	2451.06	4	612.76	5.77	0.001	0.049

CFS=Cognitive Flexibility Scale, SES=Socioeconomic Status

To examine the relationship of cognitive resilience with sociodemographic variables, ANOVA test was done, and no statistically significant relationships were observed with any variables [Table 2c].

Table 2c

Relationships of cognitive resilience with sociodemographic variables

	Sum of Squares	df	Mean Square	F	Sig.	η2
CRS Score * Designation	38.78	2	19.390	1.57	0.207	0.007
CRS Score * Education	37.51	3	12.50	1.01	0.385	0.007
CRS Score * Religion	4.66	3	1.55	0.12	0.945	0.001
CRS Score * Marital status	12.24	3	4.08	0.33	0.804	0.002
CRS Score * Family status	4.01	2	2.00	0.16	0.850	0.001
CRS Score * SES	41.44	2	20.72	1.68	0.186	0.007
CRS Score * Substance use	80.90	4	20.22	1.65	0.160	0.014

CRS=Cognitive Resilience Scale, SES=Socioeconomic Status

ANOVA test was also carried out to examine the relationships of life satisfaction with sociodemographic variables that reveal statistically no significant relationships except for Marital status (df = 3; F = 3.21; P = 0.023; η2 = 0.026 (small) and Family status (df = 2; F = 6.09; P = .002; η2 = .026 (small) [Table 2d].

Table 2d

Relationships of life satisfaction with socio-demographic variables

	Sum of Squares	df	Mean Square	F	Sig.	η2
SWLS Score * Designation	39.52	2	19.76	1.55	0.213	0.007
SWLS Score * Education	94.36	3	31.45	2.48	0.060	0.016
SWLS Score * Religion	53.01	3	17.67	1.38	0.246	0.009
SWLS Score * Marital status	121.29	3	40.43	3.21	0.023	0.021
SWLS Score * Family status	152.15	2	76.07	6.09	0.002	0.026
SWLS Score * SES	48.53	2	24.26	1.90	0.149	0.008
SWLS Score * Substance use	83.01	4	20.75	1.63	0.164	0.014

SWLS=Satisfaction with Life Scale, SES=Socioeconomic Status

Linear regression analysis (Adjusted R2 = 0.013; df = 1; F = 6.085; P = 0.014) was done to know if the score on working hours can predict the score on cognitive flexibility and resilience. When Working hours were entered as predictor variable and score on the CRS as a dependent variable, the score on Working hours predicted statistically significantly the score on CRS (beta = 0.115, t = 0.014, P = 0.004) [Table 3].

Table 3

Relationships of cognitive Resilience with working hours

Model		Unstandardized Coefficients		Standardized Coefficients Beta	t	Sig.	95% Confidence Interval for B
		B	Std. Error				Lower Bound	Upper Bound
1	(Constant)	2.815	0.078		36.193	0.000	2.662	2.968
	Working hours	0.020	0.008	0.115	2.467	0.014	0.004	0.036

a. Dependent Variable: CRS Score (Cognitive Resilience Scale). Predictor: Working hours. Adjusted R2=0.013; df=1; F=6.085; P=0.014

A multiple linear regression analysis (Adjusted R2 = 0.324; df = 4; F = 55.614; P = 0.001) was done to find if the score on age, Working hours CFS score, and CRS score (entered as predictor variables) can predict the score of SWLS (dependent variable). All predictor variables statistically significantly predicted the value of score on SWLS [Table 4].

Table 4

Relationships of life satisfaction with age, working hours, cognitive flexibility, and resilience

Model		Unstandardized Coefficients		Standardized Coefficients Beta	t	P	95% Confidence Interval for B
		B	Std. Error				Lower Bound	Upper Bound
1	(Constant)	5.238	1.627		3.218	0.001	2.039	8.43
	Age	0.054	0.023	0.089	2.320	0.021	0.008	0.09
	Working hours	-0.265	0.069	-0.150	-3.860	0.001	-0.400	-0.13
	CFS Score	0.182	0.013	0.536	13.886	0.001	0.156	0.20
	CRS Score	1.299	0.395	0.128	3.290	0.001	0.523	0.20

a. Dependent Variable: SWLS Score (Satisfaction with Life Scale); Independent Variables: CFS=Cognitive Flexibility Scale; CRS=Cognitive Resilience Scale. Adjusted R2=0.324; df=4; F=55.61; P=0.001

DISCUSSION

The study was carried out to examine the levels and relationships of cognitive flexibility and resilience with life satisfaction among IT professionals, and we could not trace any study examining these variables in IT professionals.

The demographic characteristics were like other reports from India.[4589] Interestingly, about 14% reported having substance use. Though the proportion is lesser than the previous report, it may be due to more female participants in this study.[4] Multiple job-related issues have been attributed to substance abuse among IT professionals.[6]

In this study, the level of cognitive flexibility among IT professionals was lower than college students[4844] but comparable to those with banking profession in India;[49] however, 61.7% had less than median while 38.3 had more than the median value. Result reveals the level of cognitive flexibility to have a link with religious affiliation status, marital status, family status, socioeconomic status, and substance use. Regarding religious affiliation, most participants were Hindus. So far literature is scarce of such link; on the contrary, Zmigrod et al.[50] observed that in western countries religious disbelief and reduced religious practice among religious individuals are related to heightened cognitive flexibility. The major chunk of IT professionals was characterized by the middle class, married, nuclear family. Cognitive flexibility may mediate the effects of family expressiveness and conflict[51] and lower levels may link to socioeconomic status in lower age.[5253] Habitual smoking and alcohol use may selectively impair cognitive flexibility.[5455]

The elevated level of resilience was indirectly supported by the report that emotional intelligence is higher than the general population and resilience mediates the effect of emotional intelligence to deal with stress.[56] The prolonged working hours may directly, or indirectly impair cognitive resilience as observed in this study.[57]

The mean level of life satisfaction was low in the study population. SWLS score was significantly higher for non-divorced, and single or joint families. The relationship between marital status and family status is congruent with the report that identified these factors to be an important determinant of life satisfaction among South Asians.[1618] Another study from India reported a similar level of life satisfaction among IT professionals, which positively correlated with the level of their happiness[15] and job satisfaction.[1416] As the majority were married and nearly half were female, it may have some influence of Indian culture on satisfaction. Indian IT professionals appear to receive adequate support from the spouse that would aid to it,[58] and as the majority engaged in leisure activity, it may have enhanced life satisfaction, particularly those with middle and higher socioeconomic status.[59] The positive link between life satisfaction and age appears to be consistent with other reports.[6061]

There was a negative link of life satisfaction with the working hours and is consistent with a recent report.[62] Longer working hours constrain the time to be used in other life domains,[6364] which negatively affect the satisfaction in life domains.[65] Government in different countries implement a policy to reduce the working hours to improve quality of life that may enhance life satisfaction. One should be cautious that gender difference exists due to different gender-related obligations and roles. Man with too short a working hour may have low life satisfaction.[66]

We observe a positive link between life satisfaction and cognitive flexibility and resilience. Cognitive flexibility may mediate life satisfaction.[6768] Among college students, cognitive flexibility is reportedly strongly correlated with life satisfaction.[69] It appears that cognitive flexibility enables the ability to live a life close to their valued ideals through positive mental health, and flexibility constitutes a part of life satisfaction.[70]

Life satisfaction and resilience were positively linked in this study. In college students, resilience correlated with life satisfaction.[7172] Resilience is associated with lower perceived stress[56] and enhances positive emotion and emotional balance, an important factor of life satisfaction.[727374] In other words, positive feelings (due to positive emotion) may bring a positive attitude towards evaluating one's life, resulting in higher life satisfaction. Similarly, resilience has a buffering effect on stressors resulting in a lower level of psychological discomfort.[75] Mindfulness that enhances positive effect and well-being is reported to improve resilience.[36]

CONCLUSIONS

Among Indian IT professional's cognitive flexibility and life, satisfaction is low and influenced by family. Life satisfaction is proportionately linked to cognitive flexibility and resilience.

This study has some limitations; it is a web-based study relying on snowball sampling and inability to determine the response rate and any details of non-responders. Other limitations are that there are no details of the occupational issue and other determinants of mental health. Being an initial study, further study is needed to confirm the finding.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.