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Employee well‐being outcomes from individual‐level mental health interventions: Cross‐sectional evidence from the United Kingdom

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  • William J. Fleming

Abstract

Initiatives that promote mental well‐being are formally recommended for all British workers, with many practices targeting change in individual workers' resources. While the existing evidence is generally positive about these interventions, disagreement is increasing because of concerns that individual‐level interventions do not engage with working conditions. Contributing to the debate, this article uses survey data (N = 46,336 workers in 233 organisations) to compare participants and nonparticipants in a range of common individual‐level well‐being interventions, including resilience training, mindfulness and well‐being apps. Across multiple subjective well‐being indicators, participants appear no better off. Results are interpreted through the job demands–resources theory and selection bias in cross‐sectional results is interrogated. Overall, results suggest interventions are not providing additional or appropriate resources in response to job demands.

Suggested Citation

  • William J. Fleming, 2024. "Employee well‐being outcomes from individual‐level mental health interventions: Cross‐sectional evidence from the United Kingdom," Industrial Relations Journal, Wiley Blackwell, vol. 55(2), pages 162-182, March.
    • Handle: RePEc:bla:indrel:v:55:y:2024:i:2:p:162-182
    DOI: 10.1111/irj.12418
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    References listed on IDEAS

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    1. Kristy Burns & Louise A. Ellis & Abilio De Almeida Neto & Carla Vanessa Alves Lopes & Janaki Amin, 2025. "What Is the Role of Industry-Based Intermediary Organisations in Supporting Workplace Mental Health in Australia? A Scoping Review," IJERPH, MDPI, vol. 22(7), pages 1-18, June.
    2. Jirjahn, Uwe & Mohrenweiser, Jens, 2025. "Management Practices, Workplace Health Promotion and Productivity," GLO Discussion Paper Series 1643, Global Labor Organization (GLO).
    3. Grybauskas, Andrius & Cárdenas-Rubio, Jeisson, 2024. "Unlocking employer insights: Using large language models to explore human-centric aspects in the context of industry 5.0," Technological Forecasting and Social Change, Elsevier, vol. 208(C).

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