Original Research

Intersectionality and well-being in an India-based information technology company

Anurag Shekhar, Musawenkosi D. Saurombe

Received: 09 July 2025; Accepted: 16 Sept. 2025; Published: 31 Oct. 2025

Copyright: © 2025. The Author(s). Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Orientation: While contemporary workplaces can foster structure, purpose and social connection, they can concurrently be a source of psychological distress.

Research purpose: This research examined how specific demographic factors influence workplace well-being among employees in an India-based information technology (IT) company.

Motivation for the study: Despite growing global interest in workplace well-being, evidence from non-Western contexts remains limited.

Research approach/design and method: Adopting an explanatory sequential mixed-methods design, the research integrated a cross-sectional survey (n = 109) with two focus group discussions (n = 15) and five interviews (n = 5) to explore experiences of well-being, engagement and perceived stress.

Main findings: Five constructs were quantitatively assessed: mental well-being, life satisfaction, flourishing, work engagement and perceived stress. Among 20 hypotheses tested, 2 yielded statistically significant results: life satisfaction was significantly higher among high-income employees (p = 0.011) and perceived stress differed across generational cohorts (p = 0.043), with younger employees reporting more stress. Qualitative data revealed how job demands, social identities and technostress shaped well-being experiences. Younger participants described heightened stress linked to isolation, urban commuting and reduced social interaction after transitioning from college to corporate life.

Practical/managerial implications: The findings highlight the need for culturally sensitive and demographically responsive well-being interventions in fast-evolving work environments.

Contribution/value-add: This research contributes to Global South scholarship on workplace mental well-being by showing that intersectional demographic factors significantly shape well-being outcomes.

Keywords: workplace well-being; mental health; life satisfaction; work engagement; perceived stress; intersectionality; technostress; Indian IT industry.

Introduction

The contemporary workplace presents a duality concerning mental health: it can foster structure, purpose and social connection, yet concurrently be a significant source of psychological distress. The World Health Organization (WHO, 2024) posits that conducive work environments are integral to well-being, whereas factors such as job insecurity, excessive demands or unsupportive leadership can prove detrimental. In 2019, the WHO (2022, 2024) estimated that 15% of working-age adults were living with a mental disorder. Consequently, mental health in occupational settings is not merely a public health concern but also a pressing moral and economic imperative.

The coronavirus disease 2019 (COVID-19) pandemic exacerbated a pre-existing occupational mental health crisis (Abbas, 2021). A worldwide escalation in depression and anxiety rates has been observed, particularly among young individuals and those in early-career stages (Patel et al., 2023; Solmi et al., 2022). Traditional paradigms, predominantly centred on diagnosis and therapeutic intervention, have demonstrated limited efficacy in mitigating this trend, even within high-income nations with substantial healthcare investments (Gilbert et al., 2015; Patel et al., 2023). This has prompted global health authorities to advocate for a paradigm shift towards a more holistic approach, emphasising prevention and the active promotion of psychological well-being alongside conventional treatments, including in workplace settings (Patel et al., 2023; Sivris & Leka, 2015; WHO, 2024). A substantial body of evidence affirms the effectiveness of such proactive interventions across varied populations (Carr et al., 2020, 2024; Chakhssi et al., 2018; Donaldson et al., 2019).

Nevertheless, an imbalance persists in the geographical focus of mental health research and intervention strategies, as current efforts are disproportionately concentrated within western, educated, industrialised, rich and democratic (WEIRD) societies (Hendriks et al., 2018; Prajapati & Liebling, 2022). A study conducted by Hendriks et al. (2018) specifically showed that over 87% of studies on well-being interventions originate from North America, Europe and Australasia, with less than 1% conducted in each of the sub-Saharan Africa or South Asia regions. This geographical skew inherently limits the development and validation of culturally attuned and contextually relevant interventions for other global regions.

The Indian workplace: Contextualising mental health challenges and the role of intersectionality

Contextualising how intersectionality affects mental health in the Indian workplace is essential to positioning this research within extant literature. The COVID-19 pandemic particularly exposed systemic vulnerabilities in India’s workplace well-being systems. Deloitte India’s (2022) survey of 3995 employees across 12 industries in India revealed that over 80.0% reported at least one adverse mental health symptom, predominantly depression, burnout and anxiety. Alarmingly, fewer than 25.0% of these employees felt they received adequate support from their employers (Deloitte, 2022), thus evidencing that despite a discernible increase in mental health awareness, formal workplace interventions remain underdeveloped. Research done by Sukumar and Joseph (2021) estimates that while 75.5% of Indian employees experience significant stress, only a minority have access to structured support mechanisms, such as Employee Assistance Programmes (Sarkar et al., 2024).

With its notably dynamic information technology (IT) sector, India reflects many global mental health trends while also navigating unique contextual challenges. The Gallup State of the Global Workplace report indicates that South Asia registers among the lowest well-being scores globally, characterised by high incidences of daily stress, sadness and anger (Gallup, 2024). Within India, these challenges could be particularly amplified in the fast-paced IT industry, as factors such as prolonged working hours, intense client demands and the isolating repercussions of remote work contribute to heightened psychological strain among IT professionals (Premchandran & Priyadarshi, 2018a).

Meanwhile, the distribution of the various workplace mental health outcomes is not uniform. Social identities, including gender, generational cohort, income level and educational attainment, intersect to forge distinct experiences of workplace well-being (Allen et al., 2014; Islam et al., 2021; Jameel et al., 2024). Consequently, a universal, ‘one-size-fits-all’ approach frequently fails to adequately address the compounded challenges encountered by marginalised groups (Jameel et al., 2024). For instance, low-income women in junior roles may specifically grapple with financial insecurity, gender-based societal expectations and constrained career advancement opportunities (Jameel et al., 2024).

Research problem and purpose

Despite the growing academic cognisance of intersectionality, its application within Indian organisational research remains limited (Khanna & Mukherjee, 2024). Consequently, prevailing programmes at work often overlook how demographic variables interact to influence access to resources, exposure to job demands and overall employee well-being. The business case for adopting inclusive well-being strategies is, however, compelling, as meta-analytic reviews demonstrate that targeted interventions can significantly reduce depression and anxiety among employees, while concurrently enhancing employee engagement and productivity (Gartlehner et al., 2016; Joyce et al., 2016). Investments in evidence-based treatment for common mental disorders – including in the workplace context – yield strong economic returns, as global modelling estimates a 4:1 benefit-to-cost ratio through improved productivity and reduced health losses (Baicker et al., 2010; Chisholm et al., 2016; WHO, 2016).

Against this backdrop, the present research aimed to understand how specific demographic factors affect workplace well-being among employees working in an IT organisation based in India through a mixed-methods research design. By integrating validated psychometric instruments – specifically, the Warwick–Edinburgh Mental Well-being Scale (WEMWBS), the Satisfaction with Life Scale (SWLS), the Flourishing Scale (FL), the Utrecht Work Engagement Scale (UWES), and the Perceived Stress Scale (PSS) – with qualitative data, this research specifically sought to understand how the intersecting factors of gender, generation, income and education influence overall workplace well-being. Focusing on employees at a prominent Mumbai-based technology firm, this research endeavoured to generate evidence-based, context-sensitive insights regarding workplace well-being by examining how specific demographic factors influence workplace well-being among employees in an India-based IT company. The research, therefore, contributes to informing the development of inclusive human resource (HR) strategies and the promotion of mental health equity within Indian workplaces, particularly within the IT sector.

Literature review

Mental health in India: A socio-economic and organisational imperative

India’s mental health landscape reveals a critical and complex public health challenge, shaped by socio-economic disparities, infrastructural limitations and rapid workplace transformation. The National Mental Health Survey of India (2015–2016) found that approximately 13.7% of Indians experience a mental health disorder during their lifetime, while 10.6% currently face psychological morbidity (Murthy, 2017). These figures are conservative, given the deeply entrenched stigma and significant treatment gap (defined as the share of people with a diagnosable mental disorder who received no treatment in the previous 12 months), which ranges from 70.0% to 92.0% across conditions (e.g. ~85.0% for common mental disorders, ~74.0% for severe mental disorders, ~86.0% for alcohol use disorders). Practically, this means that the majority of those who meet diagnostic criteria did not consult any formal care provider in the past year.

Alarmingly, many individuals – including in India – experiencing mental distress do not seek help because of limited awareness, societal stigma, or poor access to services (Bennett et al., 2020; Murthy, 2017). Individuals in lower-income brackets are disproportionately affected, as material insecurity and chronic financial stress remain key predictors of poor mental health (Thomson et al., 2022). Urban regions in India, while more resourced, paradoxically report higher rates of anxiety and depression, likely because of escalating work demands and lifestyle pressures (Murthy, 2017). This disparity underscores how structural inequalities (such as class, education and geography) shape mental well-being in deeply intersectional ways (Murthy, 2017; Xiong et al., 2020).

The COVID-19 pandemic intensified these challenges, not only increasing mental distress across populations but also exposing the fragility of India’s mental health infrastructure (Fenn et al., 2021). From an occupational perspective, high-pressure work sectors such as IT were particularly affected, as employees faced isolation, longer working hours and the blurring of boundaries between home and work (Banerjee & Gupta, 2024; Bharat et al., 2020). These pressures further built on pre-pandemic vulnerabilities documented by Premchandran and Priyadarshi (2018a), such as unhealthy overlaps between home and work life. Despite such evidence, countries continue to allocate an insufficient portion of their health budget to mental health services, highlighting the policy-practice disconnect (Bennett et al., 2020).

Meanwhile, the economic and occupational consequences of untreated mental health conditions are significant, as research shows that poor psychological health reduces motivation, concentration and interpersonal functioning, contributing to increased absenteeism, presenteeism and turnover intention (Feringa, 2018; Headspace, 2024; Pfeffer & Williams, 2020; Saurombe & Barkhuizen, 2022). On the other hand, studies show that employees with higher subjective well-being are more productive, engaged and resilient (Ahmed & Malik, 2019; Diener et al., 2020; Harter et al., 2020; Moscoso & Salgado, 2021). These benefits are not abstract, as large-scale meta-analyses show that highly engaged teams outperform their peers by up to five times in key business outcomes (Harter, 2024; Harter et al., 2009). Engagement and well-being, therefore, are no longer soft metrics – they are integral to organisational effectiveness (Shekhar et al., 2025a, 2025b).

In light of these patterns, employee mental health is best understood as a strategic organisational priority rather than an individual burden, particularly in Indian workplaces. The present research examines how various demographic factors (including gender, generation, income and educational attainment) relate to overall mental well-being among employees in an India-based IT organisation, thereby providing an empirical basis for targeted occupational health interventions and psychologically safe workplace practices.

Intersectionality as a lens for workplace well-being

Intersectionality theory provides a critical framework for understanding how multiple social identities simultaneously shape individuals’ experiences. As Crenshaw (2017) famously stated, ‘Intersectionality is a lens through which you can see where power comes and collides, where it interlocks and intersects.’ Rather than treating gender, class, caste, generation or education as separate sources of advantage or disadvantage, an intersectional approach examines how these factors interact to create unique workplace experiences that cannot be explained by one dimension alone. Within industrial psychology and HR research, there is growing recognition that intersectionality offers a richer understanding of workplace well-being disparities (Brown & Moloney, 2019; Gabriel et al., 2025; Lavaysse et al., 2018).

Scholars argue that workplace well-being cannot be divorced from broader systems of advantage and oppression (such as patriarchy, class hierarchy, racism, etc.) that permeate organisational structures (Gabriel et al., 2025; Jackson et al., 2021). Researchers advocate a multilevel approach: understanding how power dynamics at societal, organisational and interpersonal levels converge to affect those at different identity intersections (Saurombe & Zinatsa, 2023; Zinatsa & Saurombe, 2022). For example, Thatcher et al. (2023) call for examining how organisational practices and norms might systematically privilege the intersection of (for instance) maleness and high socio-economic status, while rendering the challenges of, say, lower-class women or older, less-educated workers invisible. Particularly, a 2023 case study of Indian workplaces by Majumder and Arora (2024) illustrates ‘invisibilisation’ processes, as, in the unorganised beauty and wellness sector, gender is highly visible (nearly all workers are women), yet this visibility ‘invisibilises’ other inequalities – the workers are mostly migrant indigenous women facing ethnic and class biases that are routinely overlooked. Such research reinforces that intersectional well-being is about more than individual differences – it is about how systems of power assign meaning and value to combinations of identities, shaping who feels safe, valued and healthy at work.

In summary, intersectionality provides a conceptual foundation to investigate variations in workplace well-being in a nuanced way. In the context of this research, it prompts us to ask: whose well-being are we examining, and how do their gender, generation, income level and education, among other identities, interact to influence their work lives? This is particularly pertinent in India’s IT sector, where global client delivery, hybrid work models, and project-based staffing result in varying job demands and resources (JD-R) that affect different employee groups in unique ways.

Theoretical framework of the research

We integrate the JD-R (Bakker & Demerouti, 2017), intersectionality (Crenshaw, 1989) and technostress (Ragu-Nathan et al., 2008) lenses into a single framework (Figure 1) that maps how JD-R and techno-stressors relate to well-being in high-demand, socio-demographically diverse India-based IT settings.

FIGURE 1: Conceptual integration of job demands–resources, intersectionality, and technostress theories in understanding workplace well-being.

At the major junction of this conceptual framework lies the JD-R model, which conceptualises workplace well-being as a function of the balance between job demands and job resources. Intersectionality Theory enriches the JD-R model by showing that the same work condition or outcome (in this case, workplace well-being) can be experienced differently based on one’s social position, such as gender, generation, income and education. For example, a young female IT professional from a lower-income background may face greater task ambiguity and less managerial support compared to a male peer with higher socio-economic privilege, not because of the job role alone but because of broader structural biases inherently imposed by their social position. The Technostress Theory is also positioned within the framework to depict the psychological strain caused by constant technology use, as IT professionals are particularly exposed to techno-stressors such as techno-invasion and techno-overload, which can independently or interactively impair well-being. These demands are often normalised in the industry but may disproportionately affect certain demographic groups, for example younger knowledge workers who believe that their entry-level software engineering jobs are at risk because of the arrival of artificial intelligence (AI).

The three theories converge on the central construct of workplace well-being. The JD-R model provides the structural map of demands and resources; intersectionality theory ensures we examine who faces which demands and why; and technostress theory adds a contemporary, sector-specific dimension that captures the digital overload characteristic of IT work. This triadic integration allows for a more precise and contextually grounded analysis of well-being variations across the different intersectional identities presented in this research including gender, generation, income and education.

This integrated conceptual framework (Figure 1) is operationalised through a mixed-methods design in which the quantitative strand tests prior developed hypotheses linking the intersectional identities to five well-being outcomes (mental well-being, life satisfaction, flourishing, work engagement, perceived stress), while the qualitative strand probes JD-R and technostress processes (e.g. techno-overload, invasion and complexity) to explain how demands and resources are produced, distributed and buffered concerning the various roles and identities.

Hypotheses development

Within the JD-R framework, lower material resources and higher chronic demands predict poorer well-being and higher stress, whereas the availability of more lucrative resources predict engagement and life satisfaction (Bakker & Demerouti, 2017). In India, mental health risk is higher among lower-income groups and in high-demand urban IT contexts (Banerjee & Gupta, 2024; Bharat et al., 2020; Murthy, 2017). Technostress can elevate strain, often more salient for younger cohorts during remote and hybrid work, while resources buffer its effects. Education may confer skills and employability (resources) but can also raise expectations and role breadth (demands), yielding mixed associations. Gendered divisions of labour and workplace norms can increase job demands and reduce income and access to resources for women in Indian workplace settings (Jameel et al., 2024). On this basis, we expected group differences (main effects) and, consistent with intersectionality, moderation whereby the effect of one demographic dimension varies by another (e.g. income by gender).

Hypotheses tested

We tested main-effect hypotheses linking four demographic factors (gender, generation, income, education) to five well-being outcomes. It is important to note that interaction effects were not estimated in the quantitative strand. Instead, the qualitative strand probed JD–R and technostress processes to explain how demands and resources are produced, distributed and buffered concerning the various roles and identities. The 20 hypotheses tested in this research are outlined as follows:

Mental well-being (WEMWBS)

  H1a: Mental well-being differs by gender.

  H1b: Mental well-being differs by generation.

  H1c: Mental well-being differs by income.

  H1d: Mental well-being differs by education.

Life satisfaction (SWLS)

  H2a: Life satisfaction differs by gender.

  H2b: Life satisfaction differs by generation.

  H2c: Life satisfaction differs by income.

  H2d: Life satisfaction differs by education.

Flourishing (FL)

  H3a: Flourishing differs by gender.

  H3b: Flourishing differs by generation.

  H3c: Flourishing differs by income.

  H3d: Flourishing differs by education.

Work engagement (UWES)

  H4a: Work engagement differs by gender.

  H4b: Work engagement differs by generation.

  H4c: Work engagement differs by income.

  H4d: Work engagement differs by education.

Perceived stress (PSS)

  H5a: Perceived stress differs by gender.

  H5b: Perceived stress differs by generation.

  H5c: Perceived stress differs by income.

  H5d: Perceived stress differs by education.

Research design

This research adopted an explanatory sequential mixed-methods approach to understand how various demographic factors, such as gender, generational cohort, income level and educational background, interact to shape employees’ well-being in the workplace. The mixed-methods design facilitated a layered understanding, combining the breadth of quantitative analysis with the depth of qualitative insight. Embedded within a broader research project, the current research specifically combined a quantitative cross-sectional survey with qualitative interviews to capture both patterns in well-being metrics and the nuanced experiences behind them.

The quantitative phase offered a broad overview of key well-being indicators, including mental health, life satisfaction, flourishing, work engagement and perceived stress, using validated scales across a diverse group of IT professionals employed by an India-based technology firm. To enrich these findings, the qualitative phase included two focus group discussions (FGDs) and follow-up semi-structured interviews with a subset of participants who had earlier taken part in a well-being training programme. Their prior involvement in the programme allowed for meaningful rapport and enabled the researcher to delve deeper into how participants interpreted and experienced well-being, especially in light of their intersecting social identities and workplace dynamics. In this article, we interpret such training exposure as contextual (not causal), while noting this as a possible limitation when it comes to its influence on the research findings.

The current research was underpinned by a constructivist ontological stance and an interpretivist epistemology, acknowledging that well-being is a fluid and context-dependent construct, shaped by individual meaning-making and the social environment. This philosophical orientation informed the qualitative strand, which foregrounded employee narratives and sense-making processes, while the quantitative component offered comparative insights across demographic groups. Together, the two strands allowed for robust triangulation, offering a well-rounded picture of how intersectionality shapes workplace well-being within the Indian corporate landscape.

Research setting

The research was conducted within a large India-based IT company headquartered in Mumbai, employing over 800 staff across multiple locations. The workforce primarily comprised of male IT engineers supporting global clients, many of whom had migrated from various parts of India. This internal mobility created a diverse demographic landscape across region, religion, caste, language, gender and sexuality, making it an ideal setting to explore the intersectionality of identity in relation to workplace well-being. The organisation’s stable employment environment and national footprint further strengthened its suitability for studying how social identities interact to shape workplace well-being outcomes.

Research participants and sampling methods

The quantitative component of the research involved 109 employees, representing a substantial and demographically diverse segment of the company’s workforce. Respondents were drawn from core IT, IT engineering and IT support functions across the various Mumbai-headquartered company office locations, providing variation across gender, generation, income level and education. This diversity mirrors the broader demographic heterogeneity of India’s technology sector, enhancing the relevance and contextual applicability of the research results.

The qualitative phase was designed to deepen the understanding of patterns emerging from the survey data. Two FGDs were conducted, comprising eight and seven participants respectively (a total of 15 participants), followed by five semi-structured, one-on-one interviews with purposively selected participants. These individuals were chosen based on demographic diversity and their willingness to share detailed personal narratives. This sequential explanatory design allowed the researcher to methodologically triangulate quantitative patterns with rich, context-specific insights into how employees interpret and experience well-being, engagement and perceived workplace stress within their organisational realities.

The demographic composition of the full survey sample is illustrated in Figure 2, which displays the distribution of respondents across gender, generational cohort, income category and educational attainment. This demographic spread enabled an intersectional analysis of how individual characteristics interact with structural and cultural workplace factors to shape workplace well-being.

FIGURE 2: Details about the respondents’ demographics.

According to Pourhoseingholi et al. (2013), sample size adequacy in cross-sectional designs depends on assumptions regarding population size, prevalence and precision. With an assumed prevalence of 0.6 and a precision of 0.10, a minimum sample size of 92 is typically sufficient for organisational-level inference. The present research, with 109 valid survey responses, comfortably exceeds this benchmark. In addition, an a priori power analysis using G*Power 3.1 (Faul et al., 2009) indicated that a minimum of 44 participants would be required to detect medium effect sizes (d = 0.50) with 80% power at a 0.05 significance level for non-parametric tests. This confirms that the current research’s sample size is well-suited to support meaningful group comparisons and correlation analysis.

Data collection methods

Quantitative data for this research were collected as part of a broader research project using a structured, cross-sectional online survey administered within a prominent India-based IT company headquartered in Mumbai. The survey was developed using internationally validated instruments and distributed in English through the organisation’s internal communication channels, with participation managed confidentially. The objective was to understand how various demographic factors affect workplace well-being among a diverse workforce.

The survey included standardised, psychometrically robust instruments frequently used in occupational psychology, as subsequently outlined. The 4-item PSS-4 is a reliable and valid tool for assessing stress (Warttig et al., 2013). Scores range from 0 to 16, with a score of ≥ 6 indicating a high level of perceived stress (Warttig et al., 2013), and its use is well-established in India (Fenn et al., 2021; Lal et al., 2025). Work engagement was measured using the ultra-short UWES-3, capturing vigour, dedication and absorption (Schaufeli & Bakker, 2004). It demonstrates sound psychometric properties and has been tested in multiple countries (Merino et al., 2021; Storm & Rothmann, 2003). The SWLS is a 5-item scale measuring the cognitive component of subjective well-being (Diener et al., 1985). It demonstrates high internal consistency and is suited for non-clinical populations. The scale has been tested in India (Dahiya & Rangnekar, 2020). Flourishing Scale provides a single score representing self-perceived success in important areas of psychological well-being (Diener et al., 2010). It has strong psychometric properties and has been used in Indian studies (Premchandran & Priyadarshi, 2018b). The WEMWBS measures positive mental health, covering both hedonic and eudaimonic aspects (Tennant et al., 2007). This scale has also been validated for use in India (Singh & Raina, 2020).

Trustworthiness

Trustworthiness was established through multiple strategies aligned with Lincoln and Guba’s (1985) criteria: credibility, dependability, confirmability and transferability. Credibility was enhanced by triangulating survey data with qualitative interviews, allowing participant narratives to contextualise and deepen the interpretation of statistical trends related to well-being, engagement and stress. Dependability was ensured through consistent data collection procedures, using validated well-being instruments and systematic tracking of response rates and attrition. Quantitative analyses were conducted using standard statistical software, while qualitative data were analysed thematically, with supervisory review to ensure analytic rigour. Confirmability was strengthened by the use of reflexive memos written after each interview and an audit trail documenting key decisions throughout the research process. Transferability was supported through rich descriptions of the intervention design, delivery modalities and participant demographics, enabling the determination of the extent to which the findings can be meaningfully applied to similar workplace well-being studies and initiatives.

Data analysis

Both quantitative and qualitative data in this research were analysed in an integrated manner to explore how intersecting demographic factors influence workplace well-being in an India-based IT company. For the quantitative strand, univariate normality for all well-being constructs was assessed using the Shapiro–Wilk test in Statistical Package for the Social Sciences (SPSS). The results revealed that while some constructs met the assumption of normality, others did not. Accordingly, a combination of parametric and non-parametric statistical techniques was adopted. Where normality held, parametric methods such as analysis of variance (ANOVA) were used; where it did not, non-parametric alternatives were applied. Specifically, the Mann-Whitney U test was used to assess differences between two groups (e.g. gender), and the Kruskal-Wallis test was employed for comparisons across multiple factors (e.g. gender, generational cohorts, income brackets and education levels). These various tests were accordingly applied to five key constructs of employee well-being: mental health (WEMWBS), life satisfaction (SWLS), flourishing (FL), work engagement (UWES) and perceived stress (PSS). Meanwhile, the qualitative strand thematically analysed the JD–R and technostress mechanisms that may explain the observed quantitative patterns. Following Braun and Clarke’s (2021) six-step approach, the transcripts were coded, and recurring patterns were organised into overarching themes. A combination of deductive and inductive (also referred to as abductive) reasoning techniques was applied during the qualitative data analysis.

Ethical considerations

Ethical approval to conduct this study was obtained from the University of Johannesburg Department of Industrial Psychology and People Management Research Ethics Committee (No. IPPM-2022-618[D]).

Results

Quantitative results

Before conducting hypothesis testing, the Shapiro–Wilk Test was used to assess the normality of distribution for each well-being variable. The results were mixed: while two constructs (WEMWBS and SWLS) followed a normal distribution, the remaining three constructs (Flourishing, UWES, and PSS) did not (see Table 1). Accordingly, a combination of parametric and non-parametric statistical tests was applied based on the distribution properties of each variable. The research specifically tested whether gender, generation, income and education were associated with the five workplace well-being constructs, in line with the 20 earlier developed hypotheses.

The results indicated that most demographic variables were not significantly associated with the well-being constructs, leading to 18 out of the 20 hypotheses being rejected in this research. However, two notable exceptions emerged:

• Life satisfaction (SWLS) showed a significant difference by income (p = 0.011), with higher-income groups reporting greater satisfaction.
• Perceived stress (PSS) showed a significant difference based on generational cohort (p = 0.043), suggesting that younger and older generations experience workplace stress differently.

These two hypotheses were, therefore, accepted. Meanwhile, no statistically significant associations were found between gender or education and any of the five constructs, nor were there significant differences for most other demographic comparisons across the remaining variables (p > 0.05). An overview of these results is outlined in Table 1.

Qualitative data

The qualitative component of this research comprised of two FGDs and five semi-structured interviews with employees across different demographic profiles and organisational roles. Although these engagements were initially designed to evaluate participant responses to a workplace well-being intervention, the narratives extended well beyond the immediate scope. Participants offered candid reflections on how their workplace experiences were shaped by job demands, social roles, technological changes and organisational support systems.

The findings from this analysis are presented in Figure 3, which visualises the emergent themes under three interlinked domains: Job Demands, Job Resources, and the cross-cutting influences of Technostress and Intersectionality. In this research, we present five qualitative themes, as subsequently outlined. Theme 1: Generational cohort and perceived stress; Theme 2: Income and well-being; Theme 3: Technostress and loneliness among younger employees; Theme 4: Strong opposition against return-to-office (RTO) policies; and Theme 5: Work–family balance strain among married women. It is important to note that themes 1 and 2 provided qualitative context for some of the key quantitative results, while themes 3 to 5 were developed from other key insights that emerged spontaneously during the FGDs and one-on-one interviews, thus substantiating the abductive reasoning techniques employed during the qualitative analysis.

FIGURE 3: Conceptual framework linking job demands, job resources, technostress, and intersectionality to workplace well-being in the India-based information technology company based on the qualitative findings.

Theme 1: Generational cohort and perceived stress

Consistent with the quantitative result showing higher perceived stress among younger cohorts, Generation Z (Gen Z) participants described acute career uncertainty amid automation and AI, thinner social networks after relocating to metros and blurred home–work boundaries under hybrid work. Long commutes were frequently cited as reducing recovery time. By contrast, older employees (mostly Millennials) acknowledged automation risks but reported that accumulated experience, broader networks, and role autonomy buffered immediate threat – helping explain the generational stress gap observed in the survey. Some of the comments were:

‘I feel like my career might get over before it even starts.’ (Participant, First FGD with 8 Participants, Male)

‘Everyone says entry-level jobs are at risk. But how will we become skilled if we don’t get to do them [the roles that enable skills acquisition] in the first place?’ (Participant, First FGD with 8 Participants, Female)

‘Since I moved to Mumbai for work, I barely see college friends…Friends made life so fun. I miss them.’ (Participant 3, One-on-One Interview, Female)

I am doing well in my job. But there is this constant fear of layoffs. How do you enjoy life with a sword hanging over your head? (Participant 2, One-on-One Interview, Male)

Theme 2: Income and well-being

Echoing the quantitative association between higher-income and greater life satisfaction, participants in higher pay bands described stabilising resources – secure housing, the ability to outsource time-intensive tasks (e.g. transport, domestic help), and more discretion over schedules or role choices – that eased day-to-day strain and supported satisfaction with life. In contrast, participants in lower pay bands more often reported shared housing, longer and less-flexible commutes and tighter budgets, which constrained time for rest, social connection and upskilling – factors they felt dampened overall life satisfaction. Some of the comments were:

‘There is no way we can afford Mumbai housing. It is more expensive than London or New York.’ (Participant, Second FGD with 7 Participants, Male)

‘Traffic is so bad. Trains are too crowded, while a car takes hours, and God forbid if it rains, we are stuck like forever.’ (Participant, Second FGD with 7 Participants, Female)

Survey means did not differ by gender for WEMWBS, SWLS, 1FS, UWES or PSS (Table 1). We therefore, addressed gendered mechanisms in the discussion rather than as a separate theme.

Theme 3: Technostress and loneliness among younger employees

This theme captures early-career perceived stress among younger employees, especially unmarried relocators to Mumbai, driven by always-on technostress (late-night client calls, constant messaging, 24/7 availability) and uneven managerial support and psychological safety, which together erode recovery time and social connection.

Several younger participants linked isolation to heightened stress and lower energy for work, which is consistent with wider evidence that low social connection is associated with poorer well-being and engagement (Pomeroy, 2019; Rojas, 2024; Twenge et al., 2021). Illustrative comments included:

‘We can never switch off. I get calls even on holidays – this is normal.’ (Participant 4, One-on-One Interview, Female)

‘I’ve developed dry eyes; I’m on screens 24/7.’ (Participant 1, One-on-One Interview, Male)

Theme 4: Strong opposition to return-to-office policies

This theme reflects widespread resistance to mandatory RTO policies. Participants reported productivity losses from commuting, office noise and interruptions, while acknowledging potential benefits of in-person days for early-career mentoring. Married women, in particular, emphasised the difficulty of balancing childcare with commuting and office presence:

‘I used to work at home in peace. Now I spend so much time in traffic, [then there is] too much noise in the office, and people keep disturbing me.’ (Participant, First FGD with 8 Participants, Female)

‘Some insecure managers want to drag everyone to the office. What’s the point?’

‘Working from the office reduces productivity and increases headaches.’ (Participant 4, One-on-One Interview, Female)

‘As a senior manager, I don’t get much advantage from coming in. But junior IT engineers can get help and guidance, so they should come regularly.’ (Participant 2, One-on-One Interview, Male)

‘In our busy city, the only way is to arrive super early and leave early – it keeps you sane and saves a tonne of time in traffic.’ (Participant, First FGD with 8 Participants, Male)

As a qualitative insight, this suggests designing hybrid arrangements that preserve mentoring (e.g. designated mentoring days, quiet zones, staggered hours) while limiting avoidable strain, rather than blanket mandates, so that practice aligns with how work is actually experienced.

Theme 5: Work–family balance strain among married women

This theme centres on work–family strain among married women, who described long commutes followed by a ‘second shift’ of unpaid care and strong cultural expectations to manage home and children:

‘It’s hard to spend so much time in traffic, then work 10 hours, and go home to start the second shift of taking care of children.’ (Participant 4, One-on-One Interview, Female)

‘The societal pressure on working women to manage home and kids is crushing.’ (Participant 3, One-on-One Interview, Female)

‘The only way I survive is with a supportive partner and household help.’ (Participant 5, One-on-One Interview, Female)

Although gender means were not significant in the survey, these interview accounts highlight intersectional pressures at the gender–marital and parental–commute nexus that matter for practice. Thus, targeted supports, flexible start and finish times, safe-travel options and caregiver assistance, should be piloted and evaluated against perceived stress and life satisfaction.

Together, these qualitative insights complement the quantitative patterns by clarifying mechanisms of stress (technostress, commuting pressures, social disconnection) and role-specific challenges (early-career support needs, gendered care responsibilities) that may not surface as survey mean differences but remain salient for practice.

Discussion

The discussion of the results and findings in this research follows the outline of the main quantitative and qualitative outcomes, with the quantitative results leading the discourse, while being interwoven with the qualitative insights.

Generational differences in perceived stress

This research revealed a statistically significant difference in perceived stress levels between generational cohorts, with younger (Gen Z) and older (Millennial) employees reporting distinct stress experiences. This indicates a meaningful divergence in stress perceptions between age groups within the India-based IT company.

Younger employees (Gen Z) in this research reported higher median stress scores compared to their Millennial counterparts, suggesting that age plays a crucial role in shaping how individuals cope with workplace demands. These generational variations may be attributed to several socio-developmental and economic factors. Younger employees are often at the early stages of their careers, navigating unstable job roles, performance pressure, loneliness and future uncertainty because of the advent of AI and resulting retrenchments. In contrast, older employees may benefit from more stable positions, higher incomes and accumulated coping resources, which together contribute to lower perceived stress.

This pattern is supported by broader empirical literature, as Charles et al. (2023), in a large-scale study, observed that younger adults report higher mental distress and lower emotional regulation compared to older adults. Positive emotions tend to rise with age, while stress and negative affect decline – a trend also confirmed by Buecker et al. (2023) in their meta-analysis of over 460 000 individuals. Buecker et al. (2023) found that well-being is typically lowest in late adolescence and early adulthood and tends to improve gradually with age, peaking in the later decades of life. This trajectory suggests that with age comes greater emotional resilience and adaptive capacity, which may partly explain the lower stress levels among older IT professionals in the current research sample.

In the Indian context, Gen Z employees may face additional stressors stemming from intense societal expectations, competitive educational and job markets, and growing financial burdens, particularly in urban areas where the cost-of-living and family support obligations are high. The transition from academic life to the high-pressure corporate environment of the IT industry may further amplify stress among younger workers (Fayard & Mayer, 2023).

These findings align with the JD-R model, which posits that employees under high job demands but lacking adequate resources, such as skill, experience, autonomy or emotional regulation skills, are more susceptible to stress and burnout (Bakker et al., 2023; Bakker & Demerouti, 2017). Gen Z professionals, with limited workplace tenure and often fewer organisational resources, may find themselves at higher risk concerning these outcomes. At the same time, Millennials in this sample may have accrued more job resources over time, including role clarity, social capital and financial stability, which serve as buffers against occupational stress. Overall, the observed generational variation in perceived stress underscores the value of designing nuanced, developmentally informed well-being interventions that align with the evolving psychological needs of a multigenerational workforce in India’s IT sector.

Income and life satisfaction

This research found a statistically significant association between income and life satisfaction, with participants in higher-income brackets reporting notably greater satisfaction with life compared to their lower-income counterparts. This finding is consistent with a substantial body of international evidence that underscores the positive relationship between financial security and well-being (Jebb et al., 2018; Killingsworth, 2021; Thomson et al., 2022).

Despite the quantitative link between income and life satisfaction, it is important to note that participants were generally hesitant to discuss income explicitly during the FGDs or one-on-one interviews. This reluctance may reflect organisational norms or formal policies that discourage open conversation about salary, directing such concerns exclusively to HR or line managers. Nevertheless, cost-of-living pressures surfaced as a shared concern, particularly among employees based in metropolitan areas such as Mumbai. Multiple participants in the FGDs referred to rising inflation, housing expenses and daily commuting costs as key financial stressors.

Gender and well-being at work in India

This research explored gender-based variations across five core workplace well-being indicators among a sample of India-based IT professionals. The analysis aimed to determine whether male and female employees experience workplace well-being differently. However, no statistically significant differences were found between genders across any of the five constructs, suggesting broadly similar well-being outcomes for men and women in this context.

These findings mirror those of Bharat et al. (2020), who conducted a large-scale survey of 896 IT engineers across India and found widespread emotional distress, with approximately 25% reporting moderate to severe stress, anxiety or depression. Similar to the present research, Bharat et al. (2020) reported no statistically significant gender or age differences; however, they identified geographical location as a key differentiator, with urban-based employees facing higher anxiety than those in smaller towns. In the present research, while gender did not yield significant mean differences, qualitative accounts from younger (Gen Z) women highlighted concerns about income and technostress, including AI-related job insecurity. These narratives suggest intersectional mechanisms at the nexus of generation, gender and income that may not surface as survey mean differences. We did not examine such intersectional interactions quantitatively because of limited subgroup sizes and power; thus, future studies should employ subgroup pre-registration and power-stratified models to test these patterns directly.

While Bharat et al. (2020) highlighted spatial differences, the present research underscores the influence of income on life satisfaction and generational cohort on perceived stress. This points to the importance of adopting a multidimensional and intersectional perspective when examining life satisfaction and stress in India’s IT sector. The lived experiences of participants in this research further illuminate how various demographic constructs (gender, generation, income and education) intersect with job demands, socio-cultural norms and family roles to affect life satisfaction and stress in ways that are not always visible in quantitative data alone.

Theoretical implications of findings

This research’s findings offer valuable insights by combining established theory with the realities of India’s IT sector. Firstly, the results strongly support the core tenets of the JD-R model. Through our group discussions, we found that excessive job demands – such as long working hours, high client expectations, the advent of AI and work overload – were associated with diminished workplace well-being, whereas abundant job resources – such as work from home facility, learning opportunities to manage threats of AI and social support– corresponded with enhanced well-being (e.g., greater job satisfaction and engagement). This demand–resource dynamic is in line with extensive prior research in organisational behaviour (Bakker & Demerouti, 2017; Tummers & Bakker, 2021). By replicating these patterns in the context of India-based IT professionals, the current research extends JD-R theory to a developing-economy, technology-intensive setting. This extension is noteworthy because much of the canonical JD-R research has emerged from Western contexts; thus, demonstrating its applicability in India bolsters the model’s cross-cultural validity (Pattnaik & Panda, 2020). Secondly, our inclusion of technostress as a specific job demand is vindicated by the qualitative data, as technostress emerged as a significant source of employee strain in this research’s analysis. This finding resonates with recent studies that identify technostress as a critical workplace stressor in knowledge-based industries (Banerjee & Gupta, 2024; Bharat et al., 2020). Thus, theoretically, we broaden the JD-R framework by empirically validating that digital-era demands can be seamlessly integrated into classic stress models, an important contribution to the extant body of knowledge as work environments become increasingly tech-centric.

There is a growing call to integrate diversity and intersectionality into occupational health models (Smith et al., 2025). In this research, we adopt an intersectional lens by (1) theorising how demographic positions shape exposure to JD-R and technostress, and (2) using qualitative enquiry to surface mechanisms across identities. In the quantitative strand, to preserve statistical power and avoid unstable estimates in sparse subgroups, we tested main effects of gender, generation, income, and education; we did not estimate fully crossed subgroup differences or higher-order interactions (e.g. Gen Z × gender). We therefore interpret demographic differences cautiously and treat the qualitative themes as explanatory context. Future research should be powered for intersectional analysis (e.g. stratified sampling, pre-registered interaction models) to estimate effects for combinations such as Gen Z women versus Gen Z men in India’s IT sector. A larger, stratified sample (with minimum cell sizes per intersectional group) and planned interaction testing (e.g. income × gender; generation × gender) would allow robust estimation of intersectional effects.

Implications for management practice

Grounded in our results (Table 1) and qualitative themes (Figure 3), the practical implications of this research focus on two evidenced levers: generation versus PSS; and income versus SWLS, as well as on qualitatively identified stressors relevant to IT work. The specific recommendations for practice emanating from this research are subsequently outlined.

When it comes to generation and PSS, higher PSS is shown among younger cohorts. Thus, managers could reduce early-career strain by setting clear after-hours boundaries; pairing Gen Z employees with mentors for role clarity and social integration; and addressing AI-related career uncertainty via transparent pathways and targeted upskilling. The effects of such interventions should also ideally be continuously tracked via PSS.

In terms of income and life satisfaction (SWLS), given higher SWLS in higher-income groups, organisations may support satisfaction for lower bands through cost-of-living sensitive benefits (such as commute support, cafeteria or meal options) and predictable progression. The effects of the provision of such benefits can also be continuously tracked using SWLS.

In terms of the additional qualitative stressors reported by participants regarding technostress (always-on messaging, late client calls), resistance to blanket RTO policies, digital-quiet-hour norms, meeting-load checks and hybrid days earmarked for mentoring rather than universal RTO can be considered. Women also described a ‘second shift’ (attending to their families after working hours) and safety during commute concerns, for which pilot options for flexible start or finish times, safe-travel support, and caregiver assistance should be considered. It is further recommended that these qualitative insights are quantitatively evaluated using PSS and SWLS.

The research findings suggest that well-being is not merely an HR initiative but a strategic imperative. As India’s IT sector becomes increasingly central to the global knowledge economy, its competitive edge will depend on maintaining the cognitive, emotional, and social well-being of its white-collar workforce. Organisational leaders should therefore embed well-being practices into the fabric of talent management by managing workloads, strengthening social support systems, addressing technostress and adopting equity-sensitive HR policies that acknowledge gender and generational differences.

Limitations and recommendations for future research

This research involved various limitations. The research’s focus on a single cultural context (India) deprived it of the possibility of comparing the research constructs across different cultural contexts. Furthermore, the research did not consider an important aspect regarding how ongoing exposure to technostress affects employee retention and overall mental health over time. In addition, while this research spanned across a large organisation in India, the inclusion of only one company limited the results’ overall generalisability to the broader Indian IT sector.

This research opens several avenues for future research. One priority is exploring how personal resources (including psychological capital, IT self-efficacy, or digital resilience) moderate the effects of technostress in high-intensity digital environments. We also recommend cross-cultural comparative research, as stress experiences and coping strategies in India’s IT industry may differ meaningfully from those in Western settings because of variations in economic precarity, collectivist norms, and organisational hierarchies. Comparative studies could help situate Indian evidence within a global dialogue on digital-era well-being.

Conclusion

This research contributes a nuanced, empirically grounded perspective on workplace well-being in India’s IT sector by integrating the JD-R model with complementary lenses of the intersectionality and technostress theories. The research findings reaffirm that while JD-R remains a robust explanatory framework, its applicability is enhanced when adapted to account for modern occupational stressors, such as AI-driven change, and demographic heterogeneity within the workforce. Specifically, the quantitative analyses showed that life satisfaction differed by income and perceived stress differed by generation (Table 1), while the qualitative accounts illuminated how workload, available support, and socio-cultural expectations shape how these differences are experienced (Figure 3). Ultimately, this research responds to the urgent scholarly and operational agenda of elevating workplace well-being as a key pillar of India’s digital transformation.

Acknowledgements

This is repetition of the last sentence in this paragraph so we have deleted it. This article is based on research originally conducted as part of Anurag Shekhar’s doctoral thesis titled, ‘Developing and evaluating a workplace training intervention to enhance well-being: A multi-methods study in South Africa and India’, submitted to the College of Business and Economics, University of Johannesburg, in 2025. The thesis was supervised by Musawenkosi Donia Saurombe. The manuscript has since been revised and adapted for journal publication. The original thesis is currently unpublished and was not publicly available online at the time of publishing this article. The authors also acknowledge Renjini Joseph who contributed to the broader study but does not meet authorship requirements for this article.

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

This article emanated from the doctoral research of A.S. who executed and wrote the article, while M.D.S was the main study leader and provided conceptualisation guidelines and editorial inputs.

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

The data that support the findings of this study are available from the corresponding author, M.D.S., upon reasonable request.

The views and opinions expressed in this article are those of the authors and are the product of professional research. The article does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or the publisher. The authors are responsible for this article’s results, findings and content.

References