COVID-19 Awareness, Technological Anxiety, and Mandatory Telework–Model Inventory

Abstract

The COVID-19 Awareness, Technological Anxiety, and Mandatory Telework—Model Inventory is an empirical psychometric instrument developed by Dr. Surabhi Verma and Dr. Vibhav Singh (2023) to assess organizational behavior, cognitive-affective appraisals, and employee performance dynamics during sudden transitions to enforced remote employment. Developed and validated in the context of Danish knowledge-sector and administrative personnel during the COVID-19 pandemic, the inventory evaluates the multi-layered socio-technical shifts experienced by the contemporary workforce. The instrument measures five distinct, theoretically grounded psychological constructs across 21 items: COVID-19 Awareness (5 items), Technological Anxiety (4 items), Attitude Towards Mandatory Telework (4 items), Work-Life Balance and Family Support (4 items), and Job Satisfaction (4 items). All items are administered using a standard five-point Likert scale ranging from 1 (“Strongly Disagree”) to 5 (“Strongly Agree”).

Psychometric evaluation utilizing structural equation modeling (SEM) and confirmatory factor analytic procedures demonstrated robust construct validity and internal consistency. Convergent validity is confirmed by average variance extracted (AVE) values spanning from 0.623 to 0.909, markedly exceeding the classical 0.50 psychometric benchmark. Discriminant validity was empirically substantiated via both the Fornell-Larcker criterion—wherein the square root of each factor’s AVE exceeded its bivariate inter-construct correlations—and the heterotrait-monotrait ratio of correlations (HTMT), with all values falling strictly beneath the conservative 0.85 to 0.90 threshold. Reliability analyses revealed high internal consistency across subscales, with Cronbach’s alpha coefficients ranging between 0.691 and 0.904, and composite reliability (CR) indices ranging from 0.866 to 0.925. Harman’s single-factor test established an absence of common method bias, with the primary factor accounting for only 32.4% of total variance. This instrument provides researchers, industrial-organizational psychologists, and occupational health practitioners with a validated diagnostic metric to evaluate digital stress, health risk perceptions, and flexible work adaptations in post-crisis and hybrid employment environments.

Keywords

COVID-19 Awareness, Technological Anxiety, Mandatory Telework, Telecommuting, Job Satisfaction, Work-Life Balance, Technostress, Structural Equation Modeling, Occupational Health Psychology, Remote Work Attitudes, Organizational Adaptation, Employee Well-Being

Authors

The inventory was conceptualized, operationalized, and psychometrically validated by:

• Dr. Vibhav Singh — Assistant Professor of Human Resource Management, School of Business Management, Narsee Monjee Institute of Management Studies (NMIMS) Deemed-to-be-University, Mumbai, India. Specialized in organizational behavior, human resource analytics, and employee coping strategies during systemic disruptions.
• Dr. Surabhi Verma — Associate Professor, Department of Business and Management, University of Southern Denmark (SDU), Odense, Denmark. ORCID: 0000-0001-7641-0637. Email: [email protected]. Specialized in digital transformation, technology adoption modeling, information systems management, and employee techno-psychology.

Purpose

The primary purpose of the COVID-19 Awareness, Technological Anxiety, and Mandatory Telework—Model Inventory is to systematically delineate, quantify, and model the psychological, cognitive, and environmental mechanisms that influence employee attitudes, behavioral responses, and subjective well-being when organizations impose mandatory remote work arrangements. Prior to global public health crises, telecommuting was predominantly examined as an elective employee perk, characterized by voluntary adoption, structured managerial oversight, and gradual socio-technical scaffolding. The sudden emergence of biological threats fundamentally inverted this paradigm, transforming telework into a compulsory, non-negotiable operational continuity measure implemented under severe psychological distress and socio-technical disruption.

Within clinical, applied organizational, and human resources contexts, this measurement tool serves three distinct analytical purposes:

1. Diagnostic Assessment of Technostress: The scale identifies specific cognitive-affective dysfunctions associated with rapid digitization, specifically isolating technological anxiety, technophobia, and fear of digital obsolescence among employees forced into remote setups without standardized technological training.
2. Occupational Health and Epidemiological Risk Appraisals: The inventory measures how objective and subjective epidemiological knowledge (COVID-19 awareness) functions as an operational antecedent that legitimizes organizational interventions, moderates stress perceptions, and buffers or exacerbates resistance to institutional change.
3. Evaluation of Hybrid Work Sustainability: By incorporating dual-domain assessments of domestic boundary management (Work-Life Balance / Family Support) alongside global workplace evaluations (Job Satisfaction), the scale enables organizational psychologists to detect early indicators of teleworker burnout, role overload, and professional isolation.

From a theoretical perspective, the inventory addresses a significant gap in the psychometric literature: the lack of unified scales capturing the intersection between public health crisis cognition, sudden information system implementation, and occupational satisfaction. Organizational decision-makers and policy architects can utilize the inventory to evaluate whether employee discontent during institutional change stems from poor software usability, domestic boundary interference, or a fundamental rejection of telecommuting policies. Consequently, the scale offers actionable empirical data for designing targeted psychological interventions, continuous digital upskilling programs, ergonomic workspace allowances, and supportive telecommuting policies across knowledge-intensive industries.

Psychological Construct

The inventory operationalizes a multidimensional conceptual model consisting of five latent psychological constructs. Each dimension measures a distinct facet of an employee’s cognitive, affective, or behavioral adaptation to crisis-induced remote work:

1. COVID-19 Awareness

This dimension evaluates the depth of an individual’s epidemiological comprehension, cognitive alertness, and behavioral vigilance regarding the SARS-CoV-2 pathogen. Rooted in health psychology and cognitive appraisal paradigms, it measures subjective knowledge regarding viral transmission vectors, symptom recognition, institutional preventive protocols, and the recognition of public health hazards. High scorers exhibit clear awareness of health advisories, comprehend disease etiology, and actively monitor epidemiological guidelines. Psychologically, this construct acts as a primary cognitive appraisal mechanism: when workers perceive a severe health hazard in the physical workplace, organizational protective measures are seen as vital survival resources rather than bureaucratic encumbrances.

2. Technological Anxiety

Technological anxiety represents an adverse affective state characterized by apprehension, psychological distress, fear, and perceived inadequacy when interacting with complex digital tools, collaborative enterprise software, and novel communication platforms. Derived from the broader clinical and occupational literature on technostress and computer anxiety, this construct captures the cognitive fear of operational failure, digital error commission, and the mental strain associated with rapid technological adaptation. Individuals exhibiting elevated technological anxiety experience pervasive worry regarding their digital self-efficacy, anticipate negative professional evaluations due to technological mishaps, and view newly mandated teleconferencing and workflow software as intimidating cognitive stressors.

3. Attitude Towards Mandatory Telework

This construct captures the employee’s evaluative disposition—spanning affective, cognitive, and behavioral dimensions—toward institutional policies requiring work-from-home execution. Rather than assessing voluntary telecommuting preferences, it targets mandatory, non-discretionary home-based labor during crisis conditions. It assesses the perceived utility of mandatory telework for maintaining occupational safety, personal health, and organizational business continuity. A favorable attitude reflects acceptance of telework as an adaptive, prosocial, and rational organizational intervention, whereas a negative attitude indicates resistance, perceived organizational overreach, and frustration with the disruption of physical workplace norms.

4. Work-Life Balance and Family Support

Drawing from ecological systems theory and boundary theory, this construct measures the degree of equilibrium, permeability management, and contextual facilitation experienced within the domestic workspace. It quantifies the employee’s perceived capacity to negotiate temporal and physical boundaries between professional labor and domestic responsibilities, alongside the instrumental and emotional support provided by family members or cohabitants. High scores denote fluid role coordination, domestic autonomy, and cooperative home environments that minimize work-to-family and family-to-work conflict, whereas low scores reflect boundary blurring, role friction, and domestic interference that erode psychological recovery.

5. Job Satisfaction

Job satisfaction within this inventory represents a global affective and evaluative orientation toward one’s ongoing employment under teleworking conditions. Reflecting established organizational psychology formulations, it assesses the perceived fulfillment, intrinsic pleasure, task accomplishment, and overall contentment derived from vocational duties executed remotely. In this context, job satisfaction functions as an overarching outcome variable indicating whether the interplay of health risk reduction, domestic boundary adjustments, and digital communication tools maintains or degrades professional morale and commitment.

Theoretical Framework

The inventory integrates three foundational theoretical paradigms: Protection Motivation Theory (PMT), the Technology Acceptance Model (TAM), and the Job Demands-Resources (JD-R) Model.

Protection Motivation Theory (PMT)

Originally formulated by R. W. Rogers (1975, 1983), PMT posits that individuals engage in protective behavioral adaptations through two cognitive mediation pathways: threat appraisal and coping appraisal. Within the framework of the inventory, COVID-19 Awareness represents the threat appraisal phase, wherein employees quantify the severity of the biological pathogen and their personal vulnerability to workplace infection. When employees possess heightened epidemiological knowledge, the physical workplace is appraised as a high-threat environment. Consequently, Mandatory Telework is perceived as an institutional coping mechanism offering response efficacy (the belief that remote work prevents infection) and self-efficacy (the confidence that one can safely work from home). PMT theoretically accounts for why higher disease awareness directly fosters favorable attitudes toward otherwise intrusive organizational mandates.

Technology Acceptance Model (TAM) and Technostress Frameworks

The technological dimension of the inventory is grounded in Fred Davis’s (1989) Technology Acceptance Model, augmented by the modern technostress paradigms articulated by Tarafdar et al. (2007) and Ragu-Nathan et al. (2008). TAM conceptualizes perceived ease of use and perceived usefulness as decisive determinants of system adoption. However, when enterprise technology adoption is mandatory rather than voluntary, low perceived ease of use manifests as Technological Anxiety. Technostress theory conceptualizes novel digital communication suites as “techno-stressors” that trigger techno-overload and techno-insecurity. Within Singh and Verma’s architecture, technological anxiety acts as an affective barrier that suppresses positive attitudes toward telework and damages overall job satisfaction by draining cognitive resources and diminishing feelings of professional competence.

Job Demands-Resources (JD-R) Model

The overarching structural integration of the model aligns with the Job Demands-Resources Model (Demerouti et al., 2001; Bakker & Demerouti, 2007). The JD-R model categorizes operational characteristics of work into job demands (aspects requiring sustained physical or psychological effort that incur physiological and psychological costs) and job resources (aspects functional in achieving goals, reducing demands, and stimulating growth). In this inventory:

• Job Demands include technological anxiety, navigating unstable domestic boundaries, and cognitive distress over epidemiological risks.
• Job Resources include robust family support, flexible scheduling autonomy, organizational continuity protocols, and health risk mitigation through home isolation.

When the job resources provided by telework and family support outweigh the technological demands and health threats, the motivational process is activated, preserving high levels of Job Satisfaction. Conversely, if technological anxiety and domestic role conflicts dominate, the health impairment process leads to psychological strain, reduced job engagement, and professional dissatisfaction.

Validity

The psychometric validity of the COVID-19 Awareness, Technological Anxiety, and Mandatory Telework—Model Inventory was empirically established through rigorous multivariate statistical testing within a cross-sectional study of Danish employees (Singh & Verma, 2023).

Convergent Validity

Convergent validity assesses the extent to which items representing a specific latent construct share a high proportion of common variance. In the validation study, convergent validity was established using two primary psychometric metrics: standardized factor loadings and the Average Variance Extracted (AVE). Following structural equation modeling, all standardized item loadings on their designated latent factors exceeded the standard 0.70 threshold (p < 0.001), demonstrating that the individual items captured substantial shared variance with their target latent constructs. Furthermore, the calculated AVE values across all five constructs ranged between 0.623 and 0.909, substantially exceeding the conservative benchmark of 0.50 proposed by Fornell and Larcker (1981). This confirms that more than 62% to 90% of the variance observed in the indicators is directly accounted for by the underlying theoretical dimensions, providing strong evidence of convergent validity.

Discriminant Validity

Discriminant validity confirms that operationalized latent constructs are statistically unique and not merely capturing reflections of other theoretical dimensions. Singh and Verma (2023) established discriminant validity through two complementary methods:

1. Fornell-Larcker Criterion: The square root of the AVE for each latent variable was systematically compared against the inter-construct bivariate correlations. In every case, the square root of the AVE was notably higher than the correlation coefficients shared between that construct and any other construct within the model. This confirmed that each construct shared more variance with its own manifest indicators than with other conceptual domains.
2. Heterotrait-Monotrait Ratio of Correlations (HTMT): To address modern psychometric critiques regarding the sensitivity of the Fornell-Larcker test, the researchers computed HTMT ratios (Henseler et al., 2015). All resulting HTMT coefficients fell comfortably beneath both the conservative 0.85 criterion and the absolute upper threshold of 0.90, confirming discriminant validity across all dimensions.

Common Method Variance (CMV)

Because all survey indicators were gathered through a single self-report instrument, common method variance was formally evaluated. Harman’s single-factor test was conducted via unrotated exploratory factor analysis (EFA). The results demonstrated that multiple distinct factors emerged with eigenvalues greater than 1.0, with the single largest factor accounting for only 32.4% of the total variance. Because this value falls well below the standard 50.0% cutoff, common method bias was confirmed to not pose a threat to the validity of the findings.

Reliability

The reliability of the inventory was evaluated using classical internal consistency analysis (Cronbach’s alpha) alongside modern structural equation modeling indices, specifically Composite Reliability (CR).

Internal Consistency and Composite Reliability

In psychometrics, while Cronbach’s alpha remains a baseline metric, it assumes tau-equivalence (equal factor loadings across all items) and often underestimates true scale reliability. Composite reliability avoids this assumption by incorporating individual standardized item loadings directly into its algorithmic calculation. The reliability parameters reported by Singh and Verma (2023) demonstrated solid internal consistency across all sub-dimensions:

• Cronbach’s Alpha (α): Scale alphas ranged from 0.691 to 0.904 across the five constructs. Values between 0.70 and 0.90 are widely considered optimal, indicating high reliability without excessive indicator redundancy.
• Composite Reliability (CR): The CR coefficients for all latent constructs ranged between 0.866 and 0.925, considerably above the accepted psychometric benchmark of 0.70 (Hair et al., 2017). This indicates that the latent constructs are consistently captured by their respective manifest indicators.

The combination of robust alpha levels and composite reliability scores confirms that the instrument possesses high measurement precision, minimal measurement error, and stable internal item intercorrelations across diverse occupational settings.

Factor Analysis

The underlying factor structure of the inventory was tested and validated through advanced multivariate statistical techniques, including confirmatory factor analysis (CFA) and structural equation modeling (SEM).

Factor Structure and Dimensionality

The initial factorial framework was developed by combining items adapted from established empirical literature (Talukder et al., 2020; Verma et al., 2020) with newly generated items designed to assess crisis-specific telework dynamics. Factor extraction confirmed a clear five-factor oblique structure, reflecting the five theoretical constructs:

• Factor 1: COVID-19 Awareness — 5 items capturing viral pathology, safety guidelines, and transmission recognition.
• Factor 2: Technological Anxiety — 4 items capturing digital distress, error apprehension, and software intimidation.
• Factor 3: Attitude Towards Mandatory Telework — 4 items capturing the acceptance and perceived efficacy of forced remote work.
• Factor 4: Work-Life Balance / Family Support — 4 items capturing domestic boundary management and household support.
• Factor 5: Job Satisfaction — 4 items capturing teleworking occupational fulfillment and task enjoyment.

Model Fit and Structural Paths

Confirmatory evaluation demonstrated that the five-factor measurement model provided a superior fit to the empirical data compared to alternative unifactorial or constrained models. The standardized factor loadings across all items were robust, with each item mapping onto its designated latent variable at statistically significant levels (p < 0.001). Structural equation paths confirmed that COVID-19 Awareness exerted a significant positive direct effect on Attitude Towards Mandatory Telework, whereas Technological Anxiety exerted a pronounced negative direct effect on attitudes and subsequent Job Satisfaction. The presence of Work-Life Balance and Family Support operated as a positive contextual facilitator that protected job satisfaction against the detrimental effects of technological anxiety.

Instrument / Measurement Tool

• Test Type: Multi-dimensional self-report inventory / psychometric questionnaire
• Intended Context: Industrial-organizational psychology, human resource management, occupational health, and remote workforce research
• Total Item Count: 21 items
• Subscales / Dimensions:
  • COVID-19 Awareness (Items 1–5)
  • Technological Anxiety (Items 6–9)
  • Attitude Towards Mandatory Telework (Items 10–13)
  • Work-Life Balance / Family Support during Telework (Items 14–17)
  • Job Satisfaction (Items 18–21)
• Administration Format: Standard digital survey, mobile-responsive web form, or paper-and-pencil questionnaire
• Target Population: Working adults, telecommuters, hybrid personnel, knowledge workers, and administrative employees across diverse industry sectors
• Completion Time: Approximately 5 to 8 minutes
• Response Format: Standard 5-point Likert scale:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Neutral / Undecided
  • 4 = Agree
  • 5 = Strongly Agree
• Scoring and Computational Procedures:
  • All items are positively worded within their respective latent domains; no reverse scoring is required.
  • Construct scores can be computed either as the arithmetic mean of the constituent items (retaining the 1 to 5 metric for practical benchmarking) or as a summation score.
  • In structural equation modeling (SEM) applications, construct scores are modeled as latent variables weighted by their standardized factor loadings.
  • Higher scores on the subscales indicate: higher epidemiological health literacy (COVID-19 Awareness), greater technostress and digital insecurity (Technological Anxiety), more favorable acceptance of mandatory remote work policies (Attitude Towards Mandatory Telework), better household boundary harmony and social support (Work-Life Balance / Family Support), and greater vocational fulfillment during remote work (Job Satisfaction).

Permissions & Fee and Test Year

The COVID-19 Awareness, Technological Anxiety, and Mandatory Telework—Model Inventory was developed and published in 2023 by Dr. Vibhav Singh and Dr. Surabhi Verma in the peer-reviewed journal Information Technology & People. The scale was established as an open academic measurement instrument designed to facilitate scholarly research in organizational psychology, management sciences, and public health workplace adaptation.

Licensing and Usage: The instrument is accessible without monetary fees for academic, scientific, non-commercial research, and educational instructional purposes. Researchers utilizing the scale are expected to provide full bibliographic attribution to the original developers by citing the seminal 2023 validation paper. Commercial organizations, management consultancies, or commercial software developers planning to incorporate the scale into proprietary employee diagnostic suites or fee-based assessment tools should contact the corresponding author, Dr. Surabhi Verma ([email protected]), to obtain formal written permission and determine licensing requirements.

References

• Bakker, A. B., & Demerouti, E. (2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22(3), 309–328. https://doi.org/10.1108/02683940710733115
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
• Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86(3), 499–512. https://doi.org/10.1037/0021-9010.86.3.499
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE Publications.
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
• Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B. S., & Tu, Q. (2008). The consequences of technostress for end users in organizations: Conceptual development and empirical validation. Information Systems Research, 19(4), 417–433. https://doi.org/10.1287/isre.1070.0165
• Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. The Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803
• Rogers, R. W. (1983). Cognitive and physiological processes in fear appeals and attitude change: A revised theory of protection motivation. In J. T. Cacioppo & R. E. Petty (Eds.), Social psychophysiology: A sourcebook (pp. 153–176). Guilford Press.
• Singh, V., & Verma, S. (2023). Impact of COVID-19 awareness and technological anxiety on “mandatory telework”: A Danish case study. Information Technology & People, 36(5), 1790–1809. https://doi.org/10.1108/ITP-12-2020-0841
• Talukder, A. K., Quazi, A., & Djebarni, R. (2020). Teleworking and work–life balance: The role of technological anxiety and family support. Computers in Human Behavior, 106, 106198. https://doi.org/10.1016/j.chb.2019.106198
• Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328. https://doi.org/10.2753/MIS0742-1222240109
• Verma, S., Gustafsson, R., & Singh, V. (2020). Digital technology usage and psychological well-being during remote work: A socio-technical perspective. International Journal of Information Management, 55, 102211.

Items of the Scale