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Editorial verdict
Methodologically cautious peer-reviewed study with mixed hypothesis support; the mediation finding on work loneliness is the credible core contribution, but cross-sectional design, single-source data, convenience sampling, and a narrow occupational context limit the generalisability of conclusions for practitioners.
Executive summary
This study investigates the psychological and behavioural consequences of GenAI-induced technostress among 290 Taiwanese public school teachers, focusing on work loneliness as a mediating mechanism and transformational leadership as a moderating boundary condition. The authors integrate the Stressor–Strain–Outcome (SSO) framework with Conservation of Resources (COR) theory to propose that GenAI-induced technostress depletes employees' resources, fostering socio-emotional disconnection (work loneliness), which in turn reduces work effort. Survey data collected between October and November 2023 were analysed using hierarchical regression, mediation analysis via PROCESS macro, and moderated mediation modelling. Key findings indicate that GenAI-induced technostress has no statistically significant direct effect on work effort, but exerts a significant indirect negative effect through work loneliness, consistent with full mediation. Transformational leadership significantly buffers the negative relationship between work loneliness and work effort, but does not significantly moderate the technostress-to-work-loneliness pathway, and the overall moderated mediation effect is non-significant. The study positions relational disconnection—rather than affective exhaustion alone—as a distinct mechanism in the technostress literature, while acknowledging limitations including cross-sectional design, convenience sampling, single-source measurement, and restricted occupational and cultural scope.
Key insights
- 1GenAI-induced technostress does not reduce work effort directly; its negative effect operates indirectly through work loneliness, suggesting that socio-emotional disconnection is the operative mechanism rather than simple cognitive overload.
- 2Transformational leadership buffers the negative relationship between work loneliness and work effort—acting as a compensatory resource—but does not attenuate the initial conversion of technostress into work loneliness, indicating the buffering function is conditional and downstream rather than preventive.
- 3The null direct effect of technostress on work effort may reflect a resource-gain offset: GenAI tools may simultaneously deplete resources through adaptation demands while generating efficiency gains, complicating simplistic assumptions about AI-stress and performance.
Practical takeaways
- Organisations monitoring AI-integration wellbeing may gain more signal by tracking indicators of relational disconnection and perceived social isolation at work, rather than focusing exclusively on cognitive overload or burnout metrics.
- Leadership development aimed at inspirational motivation, individualized consideration, intellectual stimulation, and idealized influence appears associated with sustaining employee effort under conditions of work loneliness, suggesting leadership capacity is relevant to AI-transition management.
Frameworks mentioned
Stressor–Strain–Outcome (SSO) Framework
A process model linking external stressors to psychological strain, which subsequently shapes behavioural outcomes; used here to structure the technostress–loneliness–work effort pathway.
Conservation of Resources (COR) Theory
A theory proposing that individuals strive to acquire, retain, and protect valued resources; resource threat or depletion leads to withdrawal behaviours as a protective response; used to explain the resource dynamics underlying the mediation and moderation mechanisms.
References
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- Information Systems Research (2008).The consequences of technostress for end users in organizations: Conceptual development and empirical validation.
- Information Systems Journal (2015).Technostress: Negative effect on performance and possible mitigations.
- Journal of Management Information Systems (2007).The impact of technostress on role stress and productivity.
- American Psychologist (1989).Conservation of resources. A new attempt at conceptualizing stress.
- Journal of Social Service Research (1993).A preliminary test of a stress-strain-outcome model for reconceptualizing the burnout phenomenon.
- Academy of Management Journal (2018).No employee an island: Workplace loneliness and job performance.
- Journal of Management (2023).Work effort: A conceptual and meta-analytic review.
- European Journal of Psychological Assessment (2009).Development and validation of the work effort scale.
- Research on Aging (2004).A short scale for measuring loneliness in large surveys: Results from two population-based studies.
- Lawrence Erlbaum Associates (2006).Transformational Leadership.
- The Guilford Press (2022).Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach, 3rd Edn..
- Quarterly Journal of Economics (2025).Generative AI at work.
- Science (2023).Experimental evidence on the productivity effects of generative artificial intelligence.
- Educational Technology & Society (2024).Technostress and English language teaching in the age of generative AI.
- Public Performance & Management Review (2025).Employee response to GenAI: Exploring the effect of ChatGPT dependence on work effort in a public service context.
- Journal of Applied Psychology (2003).Common method biases in behavioral research: A critical review of the literature and recommended remedies.
- Human Relations (2021).Unravelling the antecedents of loneliness in the workplace.
Source & Provenance
Not specified
Fei Liu, Minxuan Qu, Yixiao Zhang
November 5, 2026
Research Study
Asia-Pacific
Original source metadata is preserved. AI analysis is generated separately.
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