Psychological distress in high-uncertainty work: intolerance of uncertainty and multi-source social support among Chinese platform workers

Purpose Uncertainty in income, working hours and platform governance is widely documented in platform work, yet workers' capacity to tolerate future uncertainty may vary substantially. Understanding how intolerance of uncertainty relates to mental health outcomes may provide deeper insight into psychological vulnerability under structurally uncertain work conditions. This study examines levels of intolerance of uncertainty (IU), work anxiety and depressive symptoms among Chinese platform workers, and assesses whether support from family, co-workers, platforms and government/society shows distinct direct and buffering associations with these outcomes. Design/methodology/approach Using longitudinal survey data collected from 566 platform workers across 18 cities in Henan Province, China, the study describes the distribution of IU and mental health indicators and tests longitudinal associations via hierarchical OLS regressions with interaction terms. Simple-slope analyses are used to illustrate significant moderation effects. Findings Platform workers reported relatively high levels of IU, work anxiety and depressive symptoms, with vulnerability varying across socio-demographic and job groups. IU was positively associated with both work anxiety and depressive symptoms. Social support showed differentiated roles: government/society support was directly associated with lower work anxiety, whereas co-worker support and platform support attenuated the positive association between IU and depressive symptoms. Family support showed no robust associations in this sample. Practical implications Interventions should prioritise strengthening work-proximal and institutional supports, including peer networks, platform-provided assistance, and broader regulatory and societal protections, as these forms of support may be particularly consequential for reducing anxiety and uncertainty-related distress. In addition, taking into account platform workers' levels of intolerance of uncertainty may help to better understand potential vulnerability to psychological distress and inform supportive health-promotion initiatives. Originality/value The study advances understanding of platform workers' well-being by highlighting that social support is not uniform in function: support sources closer to the work process and platform governance are more likely to buffer intolerance of uncertainty and its mental health consequences, whereas more distal forms of support may be less effective in contexts of chronic uncertainty.

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Publication Details

Journal
International Journal of Workplace Health Management
Published
2026-04-27
DOI
https://doi.org/10.1108/ijwhm-01-2026-0011
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
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article

Psychological distress in high-uncertainty work: intolerance of uncertainty and multi-source social support among Chinese platform workers

X Y Wang, Pengyang Li, Qinian Chen, Qiang Li
International Journal of Workplace Health Management
Digital Economy and Work Transformation
article

Psychological distress in high-uncertainty work: intolerance of uncertainty and multi-source social support among Chinese platform workers

X Y Wang, Pengyang Li, Qinian Chen, Qiang Li
article en

Abstract

Purpose Uncertainty in income, working hours and platform governance is widely documented in platform work, yet workers' capacity to tolerate future uncertainty may vary substantially. Understanding how intolerance of uncertainty relates to mental health outcomes may provide deeper insight into psychological vulnerability under structurally uncertain work conditions. This study examines levels of intolerance of uncertainty (IU), work anxiety and depressive symptoms among Chinese platform workers, and assesses whether support from family, co-workers, platforms and government/society shows distinct direct and buffering associations with these outcomes. Design/methodology/approach Using longitudinal survey data collected from 566 platform workers across 18 cities in Henan Province, China, the study describes the distribution of IU and mental health indicators and tests longitudinal associations via hierarchical OLS regressions with interaction terms. Simple-slope analyses are used to illustrate significant moderation effects. Findings Platform workers reported relatively high levels of IU, work anxiety and depressive symptoms, with vulnerability varying across socio-demographic and job groups. IU was positively associated with both work anxiety and depressive symptoms. Social support showed differentiated roles: government/society support was directly associated with lower work anxiety, whereas co-worker support and platform support attenuated the positive association between IU and depressive symptoms. Family support showed no robust associations in this sample. Practical implications Interventions should prioritise strengthening work-proximal and institutional supports, including peer networks, platform-provided assistance, and broader regulatory and societal protections, as these forms of support may be particularly consequential for reducing anxiety and uncertainty-related distress. In addition, taking into account platform workers' levels of intolerance of uncertainty may help to better understand potential vulnerability to psychological distress and inform supportive health-promotion initiatives. Originality/value The study advances understanding of platform workers' well-being by highlighting that social support is not uniform in function: support sources closer to the work process and platform governance are more likely to buffer intolerance of uncertainty and its mental health consequences, whereas more distal forms of support may be less effective in contexts of chronic uncertainty.

International Journal of Workplace Health Management
Beijing Normal University (CN), Henan University of Technology (CN), Henan University of Engineering (CN)
Openalex Percentile: Top 3%
Digital Economy and Work Transformation
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