Abstract
Orientation: Employee and career well-being contribute to organisational performance and reflect an ethical commitment to sustainable and fair treatment of employees. In digitally mediated environments such as open distance learning (ODL), technological demands influence well-being, yet existing measurement approaches often assess these dimensions separately.
Research purpose: This study aimed to develop and validate the career and employee wellness assessment (CEWA), a comprehensive tool designed to assess six core dimensions of employee and career wellness in an academic and digitally integrated context.
Motivation for the study: As academic environments become increasingly digital and complex, institutions require a theory-informed tool to assess career and employee wellness, enabling early identification of well-being risks and targeted organisational support interventions.
Research approach/design and method: Career and employee wellness assessment was piloted at the ODL University and later implemented institutionally, with responses from 840 staff members. The newly developed scale measures six dimensions: career satisfaction, holistic wellness, career meaningfulness, digital and career wellness, career embeddedness, and employee relational wellness. Its psychometric properties were assessed using exploratory factor analysis, confirmatory factor analysis, and Rasch analysis.
Main findings: Career and employee wellness assessment demonstrated strong internal consistency, construct validity and reliability across all dimensions.
Practical/managerial implications: The instrument provides organisations with structured well-being data to inform targeted employee support and wellness initiatives.
Contribution/value-add: The CEWA contributes to the assessment of employee wellness by combining career, relational and holistic dimensions within a single measure designed for digitally mediated academic work contexts.
Keywords: employee wellness; career satisfaction; digital work environment; open distance learning; psychometric validation; multidimensional assessment.
Introduction
Digitally enabled academic environments place substantial demands on employees, including intensified technology use, dispersed role expectations and reduced opportunities for interpersonal engagement. These pressures highlight limitations in existing single-factor wellness instruments such as the Perceived Stress Scale (Cohen et al., 1983), the Maslach Burnout Inventory (Maslach & Jackson, 1981) and the Digital flourishing Scale (Janicke-Bowles et al., 2023), which each assess only narrow aspects of well-being.
Within African open distance learning (ODL) institutions, remote work practices and increasing digital workloads are central features of the employment context. In such settings, employee wellness and career satisfaction (CS) are fundamental to organisational effectiveness and sustainability (Ballard et al., 2025; Bokamoso et al., 2024; Coetzee & Schreuder, 2016; Dhanpat et al., 2025; Marsh et al., 2024; Stander, 2023; Wang et al., 2021). These contextual pressures highlight the need for a comprehensive wellness framework that incorporates psychological, social, physical and digital dimensions.
The career and employee wellness assessment (CEWA) pilot study responds to this need by validating a six-factor wellness model grounded in career embeddedness (CE) theory (Mitchell et al., 2001), holistic wellness (HW) perspectives (Myers & Sweeney, 2005) and organisational behaviour theory (Robbins & Judge, 2019).
Existing measures of employee well-being often focus on isolated constructs such as stress, burnout or digital behaviour and rarely capture the interplay among career development, digital work demands and relational support within modern work settings. The CEWA addresses this limitation by integrating career progress, HW, meaningful work, digital functioning, organisational fit and relational support within a consolidated framework relevant to digitally intensive academic contexts (Shifrin & Michel, 2022). This perspective enables organisations to better understand how changing digital work demands interact with broader dimensions of employee well-being.
Literature review
Employee wellness has increasingly been viewed through frameworks combining CS, mental health and social support (Danna & Griffin, 1999). In ODL settings, where digital pressures and isolation are prevalent, assessments like the CEWA address these complex, context-specific wellness needs (Coetzee & Schreuder, 2016).
Research commonly distinguishes between hedonic well-being, which emphasises pleasure and positive affect, and eudaimonic well-being, which focuses on meaning, purpose and human potential (Ryan & Deci, 2001). Clarifying how these paradigms inform wellness assessment is essential for conceptual coherence. Positioning this study within the hedonic–eudaimonic framework conceptualises employee well-being as encompassing both immediate affective experiences and enduring, meaning-based dimensions of personal growth, particularly within digitally mediated academic contexts (Ryan & Deci, 2001).
Career satisfaction
Career satisfaction, a central component of subjective career success, reflects individuals’ subjective evaluation of their career progress and experiences (Coetzee & Bergh, 2009; Greenhaus et al., 1990). Career satisfaction forms part of a broader network of work-related attitudes informed by social exchange and attitudinal consistency theories. As an overall evaluation of career progress, it influences organisational commitment and retention (Judge et al., 2001; Nienaber et al., 2011). When employees perceive alignment between career development and organisational support, turnover intentions decline (Ng et al., 2005). Conversely, unmet expectations may increase withdrawal cognitions (Mortimer, 2023). In South Africa’s knowledge sectors, CS also predicts engagement and retention (Coetzee, 2014; Rothmann & Hamukang’andu, 2013).
Career meaningfulness
Career meaningfulness (CM) refers to the perception that one’s work is purposeful and aligned with personal values, contributing to higher levels of engagement and psychological well-being (Bokamoso et al., 2024; Dhanpat et al., 2025; Mayer, 2011; Rosso et al., 2010; Steger et al., 2012; Theron & De Bruin, 2021). When employees view their work as meaningful and value-consistent, they are more likely to demonstrate sustained involvement, resilience and emotional commitment. For this reason, CM is included as a key dimension of the CEWA, reflecting its role in strengthening resilience and organisational commitment (Allan et al., 2019; Lesabe & Nkosi, 2007).
Holistic wellness
The indivisible self model conceptualises wellness as a composite system encompassing physical, psychological, social and spiritual aspects of functioning (Myers & Sweeney, 2004, 2005). Building on this perspective, the present study situates holistic well-being within the work context through the CEWA. The instrument operationalises wellness by assessing dimensions such as CS, meaningful work, resilience and organisationally embedded attitudes, thereby translating comprehensive wellness principles into measurable workplace constructs (Myers & Sweeney, 2004, 2005).
Within the South African organisational context, this applied perspective informs initiatives aimed at addressing demanding work conditions and promoting sustainable employee functioning (Bokamoso et al., 2024; Carrim et al., 2024; Dhanpat et al., 2025). Related frameworks, such as positive emotion, engagement, relationships, meaning, and accomplishment (PERMA) and the Job Demands–Resources model, also advocate multidimensional approaches to workplace well-being, particularly in hybrid and digitally enabled environments (Attridge, 2009; Marais et al., 2024). Empirical evidence indicates that incorporating comprehensive wellness frameworks into organisational strategies enhances engagement, resilience and employee retention in knowledge-intensive sectors.
Digital and career wellness
Digital and career wellness (DGC) describes the ability of employees to maintain psychological stability, continue professional development and function effectively in digitally mediated work environments. It involves managing digital demands through regulating screen exposure and connectivity, preserving emotional and psychological well-being amid continuous virtual interaction and aligning digital work practices with long-term career goals and meaningful professional growth (Babu & Joseph, 2025).
As workplaces globally, including those in South Africa, become increasingly digitised, employees experience growing demands associated with constant connectivity, prolonged screen exposure and blurred work–life boundaries, which contribute to psychological strain (Babu & Joseph, 2025; Marsh et al., 2024; Montag & Walla, 2016). Emotional well-being relates to the regulation of everyday affective experiences, while psychological well-being encompasses deeper dimensions such as purpose, personal growth and self-realisation that support sustained career development. In digitally intensive contexts such as ODL institutions, DGC therefore extend beyond the management of stress to include adaptability, resilience and professional flourishing (Ballard et al., 2025; Bokamoso et al., 2024; Dhanpat et al., 2025). South African research further highlights the psychosocial implications of unmanaged technological boundaries in academic and remote work settings (De Wet & Koekemoer, 2016; Shifrin & Michel, 2022). Promoting DGC is consequently critical for mitigating burnout and disengagement while supporting sustainable performance and career continuity.
Career embeddedness
Career embeddedness refers to the extent to which employees feel connected to their organisation through interpersonal links, alignment with organisational values and the perceived costs associated with leaving (Mitchell et al., 2001). Although often examined in relation to turnover intentions, embeddedness also represents a broader psychological condition associated with workplace well-being. Strong interpersonal connections, perceived compatibility between personal and organisational values and a sense of reciprocal commitment contribute to feelings of belonging, stability and professional continuity (Bokamoso et al., 2024; Dhanpat et al., 2025; Lee et al., 2004; Musakuro & Gie, 2024).
Within South African sectors such as academia, healthcare and the public service, CE has been linked not only to employee retention but also to increased engagement, organisational commitment and resilience (Takwira et al., 2014). From a wellness perspective, these elements represent relational security and contextual support that sustain long-term occupational functioning. Consequently, its inclusion in the CEWA is theoretically justified, as it captures relational and contextual aspects of career well-being essential for sustainable organisational functioning (Allen, 2006; Botha & Mostert, 2014; Takawira et al., 2014).
Employee relational wellness
Employee relational wellness (ERW) is conceptualised within the CEWA framework as a latent dimension reflecting trust, social support, professional networks and psychological safety in the workplace (Rhoades & Eisenberger, 2002; Ryan & Deci, 2001). Drawing on Self-Determination Theory and the Perceived Organisational Support model, supportive organisational environments foster motivation and contribute to employee well-being (Eisenberger & Stinglhamber, 2011). Strong relational connections have been shown to reduce emotional exhaustion and strengthen commitment in demanding sectors such as academia and healthcare (Chiaburu & Harrison, 2008; Maake et al., 2024; Musakuro & Gie, 2024). Within CEWA, relational wellness reflects the quality of interpersonal workplace experiences shaped by collegial support, mentoring and organisational culture (Bokamoso et al., 2024; Dhanpat et al., 2025).
From this perspective, CS, CM and HW represent interconnected dimensions of employee wellness reflecting alignment between purpose, resilience and occupational functioning. Career and employee wellness assessment assesses these dimensions while recognising contextual influences such as digital work demands, CE and relational dynamics (Bialowolski & Weziak-Bialowolska, 2021). This combined perspective helps explain how different aspects of employee wellness interact and contribute to a broader understanding of sustainable functioning in digitally mediated workplaces.
Research design
Research objective
The research objective is to produce a psychometrically robust tool that captures six dimensions of CEWA. Methodological steps include: (1) determining the factorial structure through exploratory and confirmatory factor analysis (CFA), (2) evaluating internal consistency and item performance via Rasch modelling and (3) confirming construct validity and practical relevance to guide organisational support and wellness initiatives within the higher-education sector and advance research on digital staff well-being.
Research method
This study used a quantitative, cross-sectional survey design to develop and validate the CEWA scale. Phase one involved creating the instrument based on wellness psychology, CE and organisational behaviour theories, with expert review ensuring content validity. After being piloted within the field of Industrial and Organisational Psychology, the refined CEWA was administered to 840 academic and administrative staff from Africa’s largest ODL institution. Psychometric evaluation included exploratory and confirmatory factor analyses, Rasch analysis and internal consistency via Cronbach’s alpha, assessing CEWA’s validity and reliability in digitally mediated academic contexts.
Research participants
A stratified random sample ensured proportional representation of academic and administrative staff, enabling meaningful comparison between occupational groups within the ODL institution. A stratified random sample of 840 employees was drawn from Africa’s largest ODL institution, yielding a near-even split between administrative personnel (51%) and academic staff (49%), proportionally represented across both strata Participants represented all career phases: early life-career employees aged 31–45 years formed the largest group (39%, n = 320), mid-career employees aged 46–56 years accounted for 36% (n = 296) and late-career employees aged 57 + years comprised 21% (n = 190); an additional 4% (n = 34) were younger than 30.
The sample was predominantly female (65%, n = 580), with males making up 33% (n = 260); one respondent identified as non-binary or third gender and four declined to state their gender. Racially, 58% (n = 515) identified as black African, 31% (n = 276) as white, 5% (n = 21) as Coloured and 4% (n = 17) as Indian, while 11 participants withheld this information. Occupationally, administrative staff constituted 51% (n = 424), academics 40% (n = 376), management 7% (n = 33) and a small fraction (2%, n = 7) identified as both employees and students.
Measuring instrument
The CEWA was designed to evaluate six core dimensions of career and employee wellness. The instrument comprises six subscales: (1) Career Satisfaction, which includes six items, such as ‘I feel positive about my career’; (2) Holistic Wellness, consisting of 13 items, for example, ‘I like my current career progress within the organisation’; (3) Career Meaningfulness, measured through three items, such as ‘My career is a result of my personal choices’; (4) Digital and Career Wellness, encompassing eight items, including ‘I always set boundaries from digital usage to maintain a healthy tech-life balance’; (5) Career Embeddedness, assessed through five items, ‘I feel positive about the network of career development support structures offered by the organisation’; and (6) Employee Relational Wellness, which includes seven items such as ‘I believe there is open and effective communication between management and employees in my organisation’. The assessment was initially piloted within the Department of Industrial and Organisational Psychology of the ODL university and subsequently administered at the institutional level.
Research procedure
Participants received an electronic survey link via email. Responses were initially captured in Excel and subsequently imported into SPSS (Version 28) and SAS/STAT® 9.4M5© (2017) for analysis. Descriptive statistics and bivariate correlations were computed using SPSS, while confirmatory factor analyses were conducted in SAS/STAT with PROC CALIS. Statistical significance was evaluated at the 5% level (α = 0.05) with results interpreted using 95% confidence intervals. Construct validity was assessed through CFA using established fit indices (comparative fit index [CFI] > 0.90; root mean square error of approximation [RMSEA] and standardised root mean square residual [SRMR] < 0.08; χ2/df < 5.0) (Hoxmeier et al., 2000; Jöreskog & Sörbom, 2002). Convergent and discriminant validity were evaluated using average variance extracted (AVE), composite reliability and heterotrait–monotrait (HTMT) criteria.
Ethical considerations
Participants received an electronic survey link sent from a no-reply email address via the university’s Information and Communication Technology (ICT) department, which served as the official gatekeeper for the study. Survey responses were initially captured in an Excel spreadsheet and subsequently converted into a Statistical Package for the Social Sciences (SPSS, Version 2017) dataset for analysis.
Ethical clearance to conduct this study was obtained from the Research Permission Sub-Committee of the Senate Research, Innovation, Postgraduate Degrees and Commercialisation Committee and the University of South Africa College of Economic and Management Sciences Research Ethics Committee (No. 2024_RPC_019 and 2020_CEMS_IOP_024). Participation in the study was voluntary, and an informed consent form was included in the online questionnaire. The principles of privacy, anonymity and confidentiality were strictly upheld throughout the research process. All participants provided informed consent for the use of group-level data for research purposes.
Results
Statistical analysis
The psychometric properties of the CEWA were examined through exploratory and confirmatory factor analyses, followed by reliability and validity assessments. Exploratory Factor Analysis (EFA) was initially conducted to empirically examine the dimensional structure and verify whether the observed data supported the proposed model. Thereafter, CFA using structural equation modelling was conducted to validate the measurement model informed by both the EFA-derived factor structure and the theoretical conceptualisation of employee wellness underpinning the CEWA. Model fit was assessed using CFI, Tucker–Lewis index (TLI) (≥ 0.90) and RMSEA, SRMR (≤ 0.08). Because Rasch Item Response Theory (IRT) models assume approximate unidimensionality, factor analytic procedures were first used to verify that each CEWA subscale represented a coherent latent dimension before Rasch analysis was conducted. After coherent latent dimensions were established, Rasch analyses were conducted for each subscale to evaluate item functioning and measurement properties within the respective wellness domains prior to assessing item fit, reliability and difficulty. Internal consistency was confirmed with Cronbach’s alpha values ranging from 0.79 to 0.91. Construct and discriminant validity were examined through inter-factor correlations and composite reliability, providing robust evidence of CEWA’s validity within an ODL context.
Table 1 presents the descriptive statistics and internal consistency reliability indices for each of the CEWA subscales.
| TABLE 1: Descriptive statistics and reliability indices for the career and employee wellness assessment subscales. |
Career and employee wellness assessment items were rated on a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).
Latent factor scores were standardised during analysis; therefore, Table 1 reports standardised scores centred around zero rather than raw scale means. All six subscales demonstrated acceptable to strong internal consistency, with Cronbach’s alpha values ranging from 0.791 to 0.906. Restricted EFA indicated approximate unidimensionality, with items clustering around a single factor. Item loadings met recommended thresholds, and no meaningful cross-loadings were observed. Career satisfaction and HW showed the highest reliability (α = 0.906). Convergent validity was supported as CS and CM exceeded the AVE threshold of 0.50.
Career embeddedness and ERW displayed acceptable reliability (α = 0.791 and 0.837), though their AVE values (0.461 and 0.440) were slightly below the ideal threshold, suggesting potential for refinement in future iterations to improve clarity and conceptual alignment. However, they were retained because of their theoretical relevance and acceptable reliability levels. Digital and career wellness demonstrated strong reliability (α = 0.889; ω3 = 0.853) and marginal convergent validity (AVE = 0.502). Career meaningfulness maintained solid internal consistency (α = 0.824) with strong validity. Pearson reliability coefficients ranged from 0.70 to 0.89 across subscales, with HW achieving the highest (0.89), indicating the scale’s ability to distinguish varying wellness levels among individuals and supporting its utility in academic environments.
The interrelationships among the CEWA subscale dimensions were examined using bivariate correlations, as summarised in Table 2.
| TABLE 2: Bivariate correlations among the career and employee wellness assessment subscale scores calculated from item responses. |
The observed correlations (r = 0.189–0.557) indicate moderate positive associations among the six CEWA wellness dimensions: CS, HW, CM, DGC, CE and ERW, supporting their discriminant validity while reflecting theoretical interconnectedness within a holistic employee wellness framework. These results support the conceptual distinctiveness of each construct while confirming their interrelatedness, as presented in Table 3, and the discriminant validity indices to confirm distinctiveness statistically.
| TABLE 3: Discriminant validity statistics for the career and employee wellness assessment dimensions (average variance extracted, square root of average variance extracted and heterotrait–monotrait ratios). |
The strongest correlations emerged between CE and ERW (r = 0.557) and between CS and ERW (r = 0.518), underscoring the significance of relational support in shaping career experiences. Moderate correlations between CE and DGC (r = 0.456) and between CS and CE (r = 0.496) further highlight the role of digital well-being and embeddedness in sustaining CS.
Descriptive statistics for the CEWA subscales are presented in Table 1. Restricted EFA was used to examine dimensionality and supported approximate unidimensionality of the subscales.
Reliability estimates were subsequently calculated, followed by CFA to evaluate the proposed six-factor measurement model. Intercorrelations among the CEWA dimensions are reported in Table 2. Table 3 presents the AVE, the square root of AVE (√AVE) and the HTMT ratios. All AVE values exceeded 0.50, supporting convergent validity. The √AVE values exceeded inter-construct correlations, and HTMT ratios were below 0.85, confirming discriminant validity and supporting the distinctiveness of the CEWA dimensions.
Exploratory factor analysis using principal axis factoring with oblimin rotation was performed to investigate the underlying structure of the CEWA items and to evaluate whether a common factor could account for the observed item covariances. The corresponding factor loadings and uniqueness estimates are reported in Table 4.
| TABLE 4: Exploratory factor analysis loadings for the career and employee wellness assessment. |
Item labels reflect the broader conceptual domains of the CEWA instrument. Subscale dimensionality analyses indicated approximate unidimensionality. Exploratory factor analysis using principal axis factoring with oblimin rotation examined the empirical structure, followed by CFA to test the hypothesised six-factor model and its alignment with the employee wellness framework.
The exploratory analysis produced a one-factor solution explaining 29.9% of the total variance. Examination of the residual correlation matrix revealed several residuals exceeding 0.05, indicating that a unidimensional model did not adequately represent the data. This evidence supported the need for additional factors, leading to the extraction of a multidimensional solution consistent with the CEWA’s theoretical structure. Although this falls below the conventional 50% benchmark for strong unidimensionality (Kaiser, 1974), it suggests a shared underlying structure warranting further examination. Most items demonstrated moderate factor loadings, with the highest loading observed for Career-positive-affective Q-5 (0.740) and the lowest retained loading for EconomicQ-3 (0.327). The one-factor solution showed poor model fit, with numerous residual correlations exceeding 0.05, indicating that a unidimensional structure did not adequately represent the data. Confirmatory factor analysis was then performed to test the hypothesised six-factor measurement model of the CEWA, consistent with the instrument’s theoretically defined multi-component structure.
Several items showed low loadings (<0.40) or high uniqueness values, such as Career_embeddednessQ_3 (0.918) and EconomicQ_3 (0.893), suggesting item-specific variance or underdeveloped subdomains. Nevertheless, their inclusion may be theoretically justified pending confirmatory testing. Importantly, the single-factor structure accounted for less than 50% of the variance, mitigating concerns of common method bias (Podsakoff et al., 2003). Although the exploratory analysis identified a dominant factor, the variance accounted for was relatively modest, and the CEWA was conceptually designed to represent several distinct dimensions of employee wellness. Examination of the residual correlation matrix indicated that the single-factor solution did not sufficiently account for the observed relationships among the items, aligning with the CEWA’s theoretically proposed multi-component structure. Confirmatory factor analysis was subsequently conducted to evaluate the hypothesised six-factor measurement model of the CEWA.
Table 5 presents the CFA estimates for the CEWA. The overall fit of the CFA model was first evaluated to determine whether the proposed measurement structure adequately represented the data. Fit indices, including χ2, CFI, TLI, RMSEA and SRMR, indicated acceptable model fit. Following the EFA, two items from the original 42-item CEWA scale were removed because of low loadings and cross-loading concerns. The CFA was subsequently conducted on the remaining 40 items, and the standardised factor loadings and model fit indices for the six-factor model are reported in Table 5.
| TABLE 5: Confirmatory factor analysis estimates for the career and employee wellness assessment. |
The CFA tested the hypothesised six-factor CEWA model using robust maximum likelihood estimation when Mardia’s coefficient indicated slight non-normality. The reported means reflect standardised latent factor scores derived from the measurement model and are centred around zero, which may result in negative values. The CFA results (Table 5) provide strong empirical support for the multidimensional structure of the CEWA Scale as a measure of the employee wellness construct, comprising six latent dimensions: CS, HW, CM, Digital and career wellness (DCW), CE and ERW. Most standardised factor loadings exceeded the recommended threshold of 0.50 (Hair et al., 2010), indicating sound convergent validity.
Model fit indices were first examined to assess the adequacy of the hypothesised six-factor CEWA measurement model before interpreting the estimated factor loadings. The hypothesised six-factor CEWA measurement model demonstrated acceptable fit to the data (CFI = 0.94, TLI = 0.94, RMSEA = 0.074, SRMR = 0.081). With acceptable model fit established, standardised factor loadings and reliability estimates were examined to evaluate the strength of the measurement indicators. The CS items loaded strongly on the latent factor, with Career_positive_affectiveQ_5 (0.854) and Career_positive_affectiveQ_3 (0.797) showing particularly strong associations. Holistic wellness also demonstrated robust loadings, particularly PersonalQ_3 (0.733) and Q_4 (0.737), capturing emotional and economic well-being. Career meaningfulness showed strong internal consistency, with loadings above 0.722 and Career meaningfulnessQ_2 reaching 0.891, suggesting it is a particularly reliable item.
All completely standardised factor loadings were statistically significant (p < 0.001), indicating that the latent constructs explained substantial proportions of variance in their respective indicators. The magnitude of these loadings was examined to assess indicator performance and identify potential areas for refinement across subscales. Error variances and R2 values were also significant, supporting adequate indicator reliability and representation of the latent constructs. Inter-latent correlations (φ estimates) were evaluated by comparing their 95% confidence intervals with the square roots of the AVE. In accordance with the Fornell–Larcker criterion, each CEWA dimension explained more variance in its own indicators than it shared with other constructs.
Table 6 presents fit indices from confirmatory factor analyses comparing alternative CEWA measurement models, including a one-factor model, the hypothesised six-factor model and a second-order model. Although EFA suggested a dominant factor using the Kaiser criterion, confirmatory results showed that a single-factor structure did not adequately represent the observed covariance among items. The one-factor model demonstrated poor fit, whereas the six-factor model produced substantially improved fit indices, supporting the multidimensional conceptualisation of CEWA. Because the six dimensions were theoretically regarded as interrelated components of employee wellness, a second-order CFA was estimated to evaluate whether they could be represented by a higher-order wellness construct (Byrne, 2016; Kline, 2016).
| TABLE 6: Model fit indices for the career and employee wellness assessment confirmatory factor models. |
Discussion
This study examined the psychometric properties of the CEWA, a comprehensive instrument developed to assess employee and career wellness within Africa’s largest ODL institution. The results provide evidence of satisfactory reliability and construct validity, with the six-factor measurement model demonstrating acceptable model fit, internal consistency and discriminant validity. These findings should be interpreted within the context of digitally intensive academic work environments, where high student enrolments, continuous online teaching demands and extensive digital administration may contribute to digital fatigue, role overload and reduced interpersonal interaction (Bozkurt & Sharma, 2020; Rapanta et al., 2020). The results also contribute to the multidimensional theory by illustrating how CS, relational wellness and digital work experiences operate as interconnected aspects of employee functioning in technology-mediated academic settings.
The findings provide empirical evidence supporting the reliability and construct validity of the CEWA for assessing career and wellness functioning in organisational contexts. All six subscales demonstrated acceptable to excellent internal consistency, with CS and HW emerging as the most reliable constructs. These results align with prior research that stresses the value of interconnected well-being models in the workplace (Coetzee & Harry, 2015; Ryff & Keyes, 1995).
Exploratory factor analysis indicated that the CEWA items shared common variance; however, CFA demonstrated that a single-factor structure did not adequately represent the data. In contrast, the six-factor and second-order models showed substantially improved fit, supporting the multidimensional conceptualisation underlying the CEWA. These findings align with international and South African research emphasising the value of integrated wellness frameworks in complex work environments (Carrim et al., 2024; Shifrin & Michel, 2022). Furthermore, positive correlations among CEWA dimensions, particularly between CE, ERW and CS, highlight the importance of relational support and organisational fit in shaping meaningful career experiences (Allen, 2006; Mitchell et al., 2001). The measurement model also demonstrated satisfactory convergent and discriminant validity, supporting the complex nature of employee wellness.
According to Fornell and Larcker (1981), discriminant validity is supported when a construct accounts for greater variance in its indicators than the variance it shares with other constructs in the model. Extending this approach, Henseler et al. (2015) proposed the HTMT ratio as a more rigorous indicator of discriminant validity. In the CEWA model, all HTMT values fell below recommended thresholds, supporting the distinctiveness of the constructs. Overall, the findings support the integrated conceptualisation of employee wellness by demonstrating that career development, relational support, digital functioning and holistic well-being can be integrated within a coherent measurement framework relevant to digitally mediated work environments.
Implications and future research recommendations
The CEWA contribute to the measurement of employee wellness and career functioning in digitally mediated and knowledge-intensive environments. Its multi-layered structure enables organisations to assess diverse domains of employee experience, including relational, emotional and digital aspects of well-being. The findings indicate that strengthening relational wellness and CE may play an important role in supporting CS. Future research should examine the longitudinal stability, construct validity and measurement equivalence of CEWA across organisational sectors using multi-group CFA. Extending the scale to diverse occupational and cultural contexts will enhance its generalisability. In practice, CEWA can assist organisations in identifying specific wellness concerns and informing targeted interventions.
Conclusion
Although the findings offer strong initial support for the CEWA framework, several limitations must be noted.
The cross-sectional design restricts causal interpretation, and the use of a single institutional sample may limit the generalisability of the results. A few subscales demonstrated slightly lower-than-ideal AVE values, suggesting that certain items may require refinement to strengthen construct validity. Additionally, reliance on self-report data introduces the possibility of common method bias, despite statistical tests indicating minimal influence. Future research incorporating longitudinal designs, multiple data sources and broader sector comparisons will be valuable in further validating CEWA and enhancing its practical utility.
Acknowledgements
This article is based on data from a larger study. A related article focusing on mapping wellness to career outcomes: predictors of career satisfaction and embeddedness in Africa’s largest open distance learning institution has been published in the African Journal of Career Development, 8(1), a188. https://doi.org/10.4102/ajcd.v8i1.188. This article forms part of Nisha Harry’s research in the development of the CEWA assessment within the ODL institution.
Competing interests
The author declares that no financial or personal relationships inappropriately influenced the writing of this article.
CRediT authorship contribution
Nisha Harry: Conceptualisation, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualisation, Writing – original draft, Writing – review & editing. The author confirms that this work is entirely their own, has reviewed the article, approved the final version for submission and publication, and takes full responsibility for the integrity of its findings.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
The author confirms that the data supporting the findings of this study are available within the article.
Disclaimer
The views and opinions expressed in this article are those of the author and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The author is responsible for this article’s results, findings and content.
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