|Year : 2022 | Volume
| Issue : 2 | Page : 84-90
Level and relationships of life satisfaction with cognitive flexibility and resilience in IT professionals
Dushad Ram1, Neha Farheen Mushtaq2, Bramaramba D Honnugudi2, Muath A Alammar1
1 College of Medicine, Shaqra University, Shaqra, KSA
2 Department of Clinical Psychology, Adichunchanagiri Institute of Medical Sciences, Karnataka, India
|Date of Submission||12-Jul-2021|
|Date of Decision||05-Oct-2021|
|Date of Acceptance||09-Oct-2021|
|Date of Web Publication||4-Jul-2022|
Dr. Dushad Ram
Department of Medicine (Psychiatry), College of Medicine, Shaqra University, Shaqra
Source of Support: None, Conflict of Interest: None
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.
Keywords: Cognitive flexibility, cognitive resilience, IT professionals, life satisfaction
|How to cite this article:|
Ram D, Mushtaq NF, Honnugudi BD, Alammar MA. Level and relationships of life satisfaction with cognitive flexibility and resilience in IT professionals. Indian J Occup Environ Med 2022;26:84-90
|How to cite this URL:|
Ram D, Mushtaq NF, Honnugudi BD, Alammar MA. Level and relationships of life satisfaction with cognitive flexibility and resilience in IT professionals. Indian J Occup Environ Med [serial online] 2022 [cited 2022 Aug 14];26:84-90. Available from: https://www.ijoem.com/text.asp?2022/26/2/84/349852
| Introduction|| |
Information technology professionals often encounter emotional dissonance, work exhaustion,,, professional and role stress,, job burnout, and multiple issues related to jobs. 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., High stress is often accompanied by different psychological issues such as depression, anxiety, and insomnia,,,, 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,,, though other factors may also play a role among Asians such as age, marital status, the standard of living, and so on., Life satisfaction is “a global assessment of a person's quality of life according to his chosen criteria”. Life satisfaction is an integral part of subjective well being; hence impairment may be linked to early morbidity/mortality, and impaired job performance.
Cognitive flexibility in IT professionals may also be influenced by their occupation-related issues, though there is paucity of studies addressing this variable. The reported factors that may impair it are elevated cognitive dissonance and job burnout., Cognitive flexibility is the ability to adaptcognitive processing strategies to face new and unexpected conditions in the environment. 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. Impaired flexibility may impair learning, resilience to stress, reduced creativity, and poorer quality of life, and ultimately impaired performance.
Cognitive resilience may also be impaired, 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. Though there are different approaches to understanding resilience, here it is used as a positive personality trait that promotes adaptation, and individual attributes that can facilitate the ability to cope when confronted with stressful life events. High resilience has been associated with well-being, life satisfaction and engagement,,, tolerance of negative affect, and strengthening effects of stress. Cognitive resilience among the IT professionals may be impaired by job burnout, job stress, and prolonged workload.
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. 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. 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 –
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.
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. 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. This scale has been used in the Indian population.
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. 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.
Satisfaction with life scale (SWLS)
Diener et al. 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.
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 1]a.
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 1]b.
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 2]a.
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 2]b.
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 2]c.
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 2]d.
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].
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|
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| 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.,,, 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. Multiple job-related issues have been attributed to substance abuse among IT professionals.
In this study, the level of cognitive flexibility among IT professionals was lower than college students, but comparable to those with banking profession in India; 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. 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 and lower levels may link to socioeconomic status in lower age., Habitual smoking and alcohol use may selectively impair cognitive flexibility.,
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. The prolonged working hours may directly, or indirectly impair cognitive resilience as observed in this study.
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., Another study from India reported a similar level of life satisfaction among IT professionals, which positively correlated with the level of their happiness and job satisfaction., 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, and as the majority engaged in leisure activity, it may have enhanced life satisfaction, particularly those with middle and higher socioeconomic status. The positive link between life satisfaction and age appears to be consistent with other reports.,
There was a negative link of life satisfaction with the working hours and is consistent with a recent report. Longer working hours constrain the time to be used in other life domains,, which negatively affect the satisfaction in life domains. 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.
We observe a positive link between life satisfaction and cognitive flexibility and resilience. Cognitive flexibility may mediate life satisfaction., Among college students, cognitive flexibility is reportedly strongly correlated with life satisfaction. 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.
Life satisfaction and resilience were positively linked in this study. In college students, resilience correlated with life satisfaction., Resilience is associated with lower perceived stress and enhances positive emotion and emotional balance, an important factor of life satisfaction.,, 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. Mindfulness that enhances positive effect and well-being is reported to improve resilience.
| 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.
Authors would like to thank Yahosa, Shamaya, Hagai, Asther, Yasuas, Marias, Ashish, Akash and Mini for their moral help.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Rutner P, Riemenschneider C, O'Leary-Kelly A, Hardgrave B. Work exhaustion in information technology professionals: The impact of emotion labor. Association for Computing Machinery Special Interest Group on Management Information Systems Database: The DATABASE for Advances in Information Systems 2011;42:102-20.
Zaza S, Erskine M, Brooks S, Morris SA. Emotional dissonance and the information technology professional: A methodological replication study. AIS Trans Replication Res 2020;6:19.
Kenworthy J, Fay C, Frame M, Petree R. A meta-analytic review of the relationship between emotional dissonance and emotional exhaustion. J Appl Soc Psychol 2014;44:94-105.
Darshan MS, Raman R, Sathyanarayana Rao TS, Ram D, Annigeri B. A study on professional stress, depression and alcohol use among Indian IT professionals. Indian J Psychiatry 2013;55:63-9.
] [Full text]
Rathore S, Ahuja V. A study of role stress among the IT professionals in India: Examining the impact of demographic factors. Int J Hum Cap Inf Technol Prof 2015;6:1-3.
Shih SP, Jiang JJ, Klein G, Wang E. Job burnout of the information technology worker: Work exhaustion, depersonalization, and personal accomplishment. Inf Manag 2013;50:582-9.
Bellini CG, Palvia P, Moreno V, Jacks T, Graeml A. Should I stay or should I go? A study of IT professionals during a national crisis. Inf Technol People 2019;32:1472-95.
Suresh Babu PV, Balakrishna S. Impact of stress on IT professionals in information technology industry-A select study. Int J Hum Resource Ind Res 2017;4:32-41.
Rajeswari KS, Anantharaman RN. Development of an instrument to measure stress among software professionals: Factor analytic study. Proceedings of ACM-SIGCPR Conference, 2003, Philadelphia, Pennsylvania. Available from: http://www.portal.acm.Org
. [Last accessed on 2021 May 12].
Padma V, Anand NN, Gurukul SM, Javid SM, Prasad A, Arun S. Health problems and stress in information technology and business process outsourcing employees. J Pharm Bioallied Sci 2015;7(Suppl 1):S9-13.
Sivapriya KR, Shah PB, Ravi R. Job Stress and Psychological Problems among Women Information Technology Professionals in India. Int J Preven Curat Comm Med 2018;4.
Nayak RD. Anxiety and mental health of software professionals and mechanical professionals. Int J Humanit Soc Sci Invent 2014;3:52-6.
Arasu SK, Dhivakar R, Chakravarthi JC, Kausik M, Kumar MA. Evaluation of professional stress in IT professionals. Int J Community Med Public Health 2019;6:1079-82.
Aydıntan B, Koç H. The relationship between job satisfaction and life satisfaction: An empirical study on teachers. Int J Bus Soc Sci Res 2016;7:72-80.
Sharma M, Garg D. A comparative study of psychological distress, life satisfaction, forgiveness and happiness in private sector it professionals: An exploratory study. Int J. Indian Psychol 2016;3:49-65.
Ngoo YT, Tan EC, Tey NP. Determinants of life satisfaction in Asia: A quantile regression approach. J Happiness Stud 2021;22:907-26.
Jagodzinski W. Economic, social, and cultural determinants of life satisfaction: Are there differences between Asia and Europe? Soc Indic Res 2010;97:85-104.
Ngoo YT, Tey NP, Tan EC. Determinants of life satisfaction in Asia. Soc Indic Res 2015;124:141-56.
Shin DC, Johnson DM. Avowed happiness as an overall assessment of the quality of life. Soc Indic Res 1978;5:475-92.
Collins AL, Glei DA, Goldman N. The role of life satisfaction and depressive symptoms in all-cause mortality. Psychol Aging 2009;24:696-702.
Chughtai AA. A closer look at the relationship between life satisfaction and job performance. Appl Res Qual Life 2019;16:1-21.
Hendon M, Powell L, Wimmer H. Emotional intelligence and communication levels in information technology professionals. Comput Hum Behav 2017;71:165-71.
Robinson A. The Impact of Cognitive Dissonance and Cognitive Flexibility on Belief Systems. MA thesis. 2013.
Ruiz FJ, Odriozola-González P. The predictive and moderating role of psychological flexibility in the development of job burnout. Univ Psychol 2017;16:282-9.
Gabrys RL, Tabri N, Anisman H, Matheson K. Cognitive control and flexibility in the context of stress and depressive symptoms: The cognitive control and flexibility questionnaire. Front Psychol 2018;9:2219.
Cañas J, Quesada JF, Antolí A, Fajardo I. Cognitive flexibility and adaptability to environmental changes in dynamic complex problem-Solving tasks. Ergonomics 2003;46:482-501.
Dajani DR, Uddin LQ. Demystifying cognitive flexibility: Implications for clinical and developmental neuroscience. Trends Neurosci 2015;38:571-8.
Feng X, Perceval GJ, Feng W, Feng C. High cognitive flexibility learners perform better in probabilistic rule learning. Front Psychol 2020;11:415.
Ajitha EA. The Impact of Hope Resilience and Positive Affectivity on Quality of Work Life and Occupational Stress of Information Technology Professionals. Ph.D. theses. Karnatak University. Department of Psychology. 2017.
Staal MA, Bolton AE, Yaroush RA, Bourne LE. Cognitive performance and resilience to stress. In: Lukey B J, Tepe V, editors. Biobehavioral Resilience to Stress. Boca Raton, FL: Taylor and Francis Group, LLC; 2008. p. 259-348.
Wagnild GM, Young HM. Development and psychometric evaluation of the resilience scale. J Nurs Meas 1993;1:165-78.
Connor KM, Davidson JR. Development of a new resilience scale: The Connor-Davidson resilience scale (CD-RISC). Depress Anxiety 2003;18:76-82.
Hoge EA, Austin ED, Pollack MH. Resilience: Research evidence and conceptual considerations for posttraumatic stress disorder. Depress Anxiety 2007;24:139-52.
Harms PD, Brady L, Wood D, Silard A. Resilience and well-being. Handbook of Well-Being. Salt Lake City, UT: DEF Publishers; 2018. p. 1-12.
Sagone E, De Caroli ME. Relationships between psychological well-being and resilience in middle and late adolescents. Proc Soc Behav 2014;141:881-7.
Bajaj B, Pande N. Mediating role of resilience in the impact of mindfulness on life satisfaction and affect as indices of subjective well-being. Pers Indiv Differ 2016;93:63-7.
Rodríguez-Fernández A, Ramos-Díaz E, Fernández-Zabala A, Goñi E, Esnaola I, Goñi A. Contextual and psychological variables in a descriptive model of subjective well-being and school engagement. Int J Clin Health Psychol 2016;16:166-74.
Kotzé M, Lamb S. The influence of personality traits and resilience on burnout among customer service representatives in a call centre. J Soc Sci 2012;32:295-309.
Elqerenawi AY, Thabet AA, Vostanis P. Job stressors, coping and resilience among nurses in Gaza strip. J Clin Exp Psychol 2017;3:3.
Takács E, Barkaszi I, Altbäcker A, Czigler I, Balázs L. Cognitive resilience after prolonged task performance: An ERP investigation. Exp Brain Res 2019;237:377-88.
Gupta G, Basole A. India's information technology industry: Prospects for growth and role in structural transformation. Decision 2020;47:341-61.
New Delhi: Government of India; 2006. Household – population and housing characteristics. In: Ministry of Health and Family Welfare. NFHS – II. p. 21-51.
Martin MM, Rubin RB. A new measure of cognitive flexibility. Psychol Rep 1995;76:623-6.
Ram D, Chandran S, Sadar A, Gowdappa B. Correlation of cognitive resilience, cognitive flexibility and impulsivity in attempted suicide. Indian J Psychol Med 2019;41:362-7.
] [Full text]
Diener E, Emmons RA, Larsen RJ, Griffin S. The satisfaction with life scale. J Pers Assess 1985;49:71-5.
Johnco C, Wuthrich VM, Rapee RM. Reliability and validity of two self-report measures of cognitive flexibility. Psychol Assess 2014;26:1381-7.
Das P, Byadwal V, Singh T. Employee engagement, pay satisfaction, cognitive flexibility, compensation fairness, affective commitment and turnover intention: A comparative study of private and public sector Banks in India. Psyber News 2016;7:7-17.
Zmigrod L, Rentfrow PJ, Zmigrod S, Robbins TW. Cognitive flexibility and religious disbelief. Psychol Res 2019;83:1749-59.
Koesten J, Schrodt P, Ford DJ. Cognitive flexibility as a mediator of family communication environments and young adults' well-being. Health Commun 2009;24:82-94.
Ursache A, Noble KG. Pediatric imaging, neurocognition and genetics study. Socioeconomic status, white matter, and executive function in children. Brain Behav 2016;6:e00531.
Rosen ML, Hagen MP, Lurie LA, Miles ZE, Sheridan MA, Meltzoff AN, et al
. Cognitive stimulation as a mechanism linking socioeconomic status with executive function: A longitudinal investigation. Child Dev 2020;91:e762-79.
Nesic J, Rusted J, Duka T, Jackson A. Degree of dependence influences the effect of smoking on cognitive flexibility. Pharmacol Biochem Behav 2011;98:376-84.
Jansen JM, van Holst RJ, van den Brink W, Veltman DJ, Caan MW, Goudriaan AE. Brain function during cognitive flexibility and white matter integrity in alcohol-dependent patients, problematic drinkers and healthy controls. Addict Biol 2015;20:979-89.
Sarrionandia A, Ramos-Díaz E, Fernández-Lasarte O. Resilience as a mediator of emotional intelligence and perceived stress: A cross-country study. Front Psychol 2018;9:2653.
Virtanen M, Singh-Manoux A, Ferrie JE, Gimeno D, Marmot MG, Elovainio M, et al
. Long working hours and cognitive function: The Whitehall II study. Am J Epidemiol 2009;169:596-605.
Valk R, Srinivasan V. Work–family balance of Indian women software professionals: A qualitative study. IIMB Manag Rev 2011;23:39-50.
Tokay Argan M, Mersin S. Life satisfaction, life quality, and leisure satisfaction in health professionals. Pers Psych Care 2021;57:660-6.
Realo A, Dobewall H. Does life satisfaction change with age? A comparison of Estonia, Finland, Latvia, and Sweden. J Res Person 2011;45:297-308.
De Ree J, Alessie R. Life satisfaction and age: Dealing with underidentification in age-period-cohort models. Soc Sci Med 2011;73:177-82.
Lee H. Working hours and life satisfaction: Finding blind spots from Korean panel data. Int Rev Public Adm 2021;26:92-109.
Greenhaus JH, Beutell NJ. Sources of conflict between work and family roles. Acad Manage Rev 1985;10:76-88.
Kahn RL, Wolfe DM, Quinn RP, Snoek JD, Rosenthal RA. Organizational Stress: Studies in Role Conflict and Ambiguity. Wiley, New York; 1964.
Hobfoll SE. Conservation of resources: A new attempt at conceptualizing stress. Am Psychol 1989;44:513-24.
Schröder M. Men lose life satisfaction with fewer hours in employment: Mothers do not profit from longer employment—Evidence from eight panels. Soc Indic Res 2020;152:317-34.
Sadeghi M, Imeni F, Bavazin F. Students' satisfaction of life: Prediction based on religiosity, meaning in life and cognitive flexibility. Women's Studies Soc Psychol 2018;16:195-222.
Odacı H, Çıkrıkçı Ö, Çıkrıkçı N, Aydın F. An exploration of the associations among cognitive flexibility, attachment styles and life satisfaction. Int J Happiness Dev 2019;5:242-56.
Odacı H, Cikrikci Ö. Cognitive flexibility mediates the relationship between big five personality traits and life satisfaction. Applied Res Quality Life 2019;14:1229-46.
Lucas JJ, Moore KA. Psychological flexibility: Positive implications for mental health and life satisfaction. Health Promot Int 2020;35:312-20.
Jowkar B. [Resilience mediating role in the relationship between emotional intelligence and general intelligence and life satisfaction]. J Contemp Psychol 2007;2:3-13.
Foumany GH, Salehi J. The relationship between emotional intelligence and life satisfaction and the mediatory role of resiliency and emotional balance among the students of Zanjan University. Acta Med Mediterr 2015;31:1351-7.
Lazarus A. Relationships among indicators of child and family resilience and adjustment following the violent trauma: A community survey. J Trauma Stress 2004;16:487-94.
Armstrong AR, Galligan RF, Critchley CR. Emotional intelligence and psychological resilience to negative life events. Pers Individ Differ 2011;51:331-6.
McKay S, Skues JL, Williams BJ. With risk may come reward: Sensation seeking supports resilience through effective coping. Pers Individ Differ 2018;121:100-5.
[Table 1], [Table 2], [Table 3], [Table 4]