Models for optimal management of psychosocial risks in the workplace

• Autorzy: Bochkovskyi A. P. , Sapozhnikova N. Yu.

Identyfikatory

DOI

10.5604/01.3001.0055.1118

• Języki publikacji: EN

Abstrakty

EN

Purpose: To develop models for optimal management of psychosocial risks in the workplace, in which the minimisation criterion is the cost of developing measures to prevent the occurrence of an incident (damage to the employee's mental health), and the limitation is the probability of its occurrence. Design/methodology/approach: Analysis of regulatory documents and scientific research in the field of building and functioning of psychosocial risk management systems in organizations and mental health care in the workplace – to identify and actualise the research problem; probabilistic and statistical methods and the method of convex optimisation – to develop models of optimal psychosocial risk management in the workplace. Findings: Models for the optimal management of psychosocial risks in the workplace have been developed, the parameters of which are the level of psychosocial risk and the number of costs allocated for measures to protect the employee's mental health. The application of the developed models allows (with a probability close to 1) to establish the minimum possible amount of costs that an organization will need to ensure that the level of psychosocial risk established at the workplace for each identified psychosocial negative factor (PNF) is not exceeded (during a work shift), taking into account the random characteristics of the PNF's negative impact on the employee over time. By changing the characteristics of the model parameters, a business entity can carry out the process of optimal management of psychosocial risks in the workplace. Research limitations/implications: The effective application of the developed models in practice requires the organization to monitor the characteristics of the intensity of the negative impact on the employee of PNF identified in the workplace in accordance with the recommendations of ISO 45001:2018. Practical implications: Applying the developed models will allow the organisation to increase economic efficiency by minimising the cost of developing measures to protect employees' mental health, which can ensure (within a given probability) the prevention of incidents during the work shift. Originality/value: For the first time, models that describe the relationship between the level of psychosocial risk have been developed. It is determined by the probability of exceeding the characteristics of the intensity of the negative impact of a certain PNF within the established maximum permissible values during a work shift and the costs allocated for measures to prevent the occurrence of this risk. The task of optimal management of psychosocial risks in the workplace (within the framework of the developed models) is reduced to the task of convex optimisation according to the criterion of minimising costs while limiting the level of the corresponding risk.

Słowa kluczowe

EN

psychosocial risk; mental health of an employee; occupational health and safety; convex optimisation; economic and mathematical models

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2025
• Tom: Vol. 128, nr 2
• Strony: 72--85
• Opis fizyczny: Bibliogr. 42 poz.

Twórcy

autor

Bochkovskyi A. P.

• Department of Systems Management Life Safety, Odessa Polytechnic National University, Shevchenko ave., 1, Odessa, 65044, Ukraine

• https://orcid.org/0000-0002-4166-3148

autor

Sapozhnikova N. Yu.

• Department of Systems Management Life Safety, Odessa Polytechnic National University, Shevchenko ave., 1, Odessa, 65044, Ukraine

• https://orcid.org/0000-0001-6181-4022

Bibliografia

• [1] Workplace stress: A collective challenge, ILO, Geneva, 2016. Available from: https://www.ilo.org/meetings-and-events/workplace-stress-collective-challenge
• [2] World mental health report: transforming mental health for all, World Health Organization, Geneva, 2022. Available from: https://www.who.int/publications/i/item/9789240049338
• [3] Safety and health at the heart of the future of work: Building on 100 years of experience, ILO, Geneva, 2019. Available from: https://www.ilo.org/sites/default/files/wcmsp5/groups/public/@dgreports/@dcomm/documents/publication/wcms_686645.pdf
• [4] WHO guidelines on mental health at work, World Health Organization, Geneva, 2022. Available from: https://iris.who.int/bitstream/handle/10665/363177/9789240053052-eng.pdf?sequence=1
• [5] F. Pega, B. Náfrádi, N.C. Momen, Y. Ujita, K.N. Streicher, A.M. Prüss-Üstün, A. Descatha, T. Driscoll, F.M. Fischer, L. Godderis, H.M. Kiiver, J. Li, L.L. Magnusson Hanson, R. Rugulies, K. Sørensen, T.J. Woodruff, Global, regional, and national burdens of ischemic heart disease and stroke attributable to exposure to long working hours for 194 countries, 2000–2016: A systematic analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury, Environment International 154 (2021) 106595. DOI: https://doi.org/10.1016/j.envint.2021.106595
• [6] M.-W. Lin, Y.-T. Wang, Y. Cheng, Psychosocial Work Conditions During the COVID-19 Pandemic and Their Influences on Mental Health Risk and Intention to Leave Among Public Health Workers: A Cross-sectional and Follow-up Study in Taiwan, Safety and Health at Work 14/4 (2023) 438-444. DOI: https://doi.org/10.1016/j.shaw.2023.10.007
• [7] A.P. Bochkovskуi, N.Yu. Sapozhnikova, Minimization of the «human factor» influence in Occupational Health and Safety, Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 6 (2019) 95-106. DOI: https://doi.org/10.29202/nvngu/2019-6/14
• [8] A.P. Bochkovskуi, N.Yu. Sapozhnikova, Stochastic models of risk management of worker fatigue emergence, Journal of Achievements in Materials and Manufacturing Engineering 123/2 (2024) 72-85. DOI: https://doi.org/10.5604/01.3001.0054.6152
• [9] L.A. Derdowski, G.E. Mathisen, Psychosocial factors and safety in high-risk industries: A systematic literature review, Safety Science 157 (2023) 105948. DOI: https://doi.org/10.1016/j.ssci.2022.105948
• [10] Comprehensive Mental Health Action Plan 2013-2030, World Health Organization, Geneva, 2022. Available from: https://www.who.int/publications/i/item/9789240031029
• [11] M. Valencia-Contrera, F. Rivera-Rojas, N. Febré, Psychosocial risks at work: a growing problem with theoretical ambiguities, Salud, Ciencia y Tecnología 4 (2024) 867. DOI: https://doi.org/10.56294/saludcyt2024867
• [12] P. Dahler-Larsen, A. Sundby, A. Boodhoo, Can occupational health and safety management systems address psychosocial risk factors? An empirical study, Safety Science 130 (2020) 104878. DOI: https://doi.org/10.1016/j.ssci.2020.104878
• [13] ISO 45003:2021. Occupational health and safety management — Psychological health and safety at work — Guidelines for managing psychosocial risks, ISO, 2021.
• [14] ISO 45001:2018. Occupational health and safety management systems — Requirements with guidance for use, ISO, 2018.
• [15] R. Liu, H.-C. Liu, H. Shi, X. Gu, Occupational health and safety risk assessment: A systematic literature review of models, methods, and applications, Safety Science 160 (2023) 106050. DOI: https://doi.org/10.1016/j.ssci.2022.106050
• [16] A.P. Bochkovskуi, Improvement of risk management principles in occupational health and safety, Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 4 (2020) 94-104. DOI: https://doi.org/10.33271/nvngu/2020-4/094
• [17] Mental health at work, World Health Organization, Geneva, 2024. Available from: https://www.who.int/news-room/fact-sheets/detail/mental-health-at-work
• [18] R. Potter, S. Jamieson, A. Jain, S. Leka, M. Dollard, V. O'Keeffe, Evaluation of national work-related psychosocial risk management policies: An international review of the literature, Safety Science 154 (2022) 105854. DOI: https://doi.org/10.1016/j.ssci.2022.105854
• [19] A. Jain, ISO 45003: The first international standard on psychosocial risk management at work, Safety and Health at Work 13/Supplement (2022) S64. DOI: https://doi.org/10.1016/j.shaw.2021.12.931
• [20] J. Riegen, Psychosocial Risk Management and Accident Prevention, a New Zealand (NZ) view, Safety and Health at Work 13/Supplement (2022) S91. DOI: https://doi.org/10.1016/j.shaw.2021.12.1038
• [21] B. Weaver, A. Kirk-Brown, D. Goodwin, J. Oxley, Perceptions of psychosocial safety behaviour (PSB): Qualitative insights on workplace psychosocial safety perceptions & actions within a policing context, Safety Science 172 (2024) 106401. DOI: https://doi.org/10.1016/j.ssci.2023.106401
• [22] H.V. Neto, Assessment of psychosocial risks at work in supervisors of clothing stores during the pandemic context, Safety Science 175 (2024) 106484. DOI: https://doi.org/10.1016/j.ssci.2024.106484
• [23] R.E. Potter, M. Dollard, L. Lerouge, A. Jain, S. Leka, A. Cefaliello, National Policy Index (NPI) for worker mental health and its relationship with enterprise psychosocial safety climate, Safety Science 172 (2024) 106428. DOI: https://doi.org/10.1016/j.ssci.2024.106428
• [24] E. Steel, S.K. Malinen, K. Näswall, Improving work-related psychosocial risk management: A mixed methods evaluation of the factors influencing inspectors’ practice, Safety Science 181 (2025) 106659. DOI: https://doi.org/10.1016/j.ssci.2024.106659
• [25] T. Bailey, The Australian policy context for the management of psychosocial risks at work, Safety and Health at Work 13/Supplement (2022) S64. DOI: https://doi.org/10.1016/j.shaw.2021.12.930
• [26] L. Alves, L. Abreo, E. Petkari, M. Pinto da Costa, Psychosocial risk and protective factors associated with burnout in police officers: A systematic review, Journal of Affective Disorders 332 (2023) 283-298. DOI: https://doi.org/10.1016/j.jad.2023.03.081
• [27] K.V. Hamre, S.V. Einarsen, G. Notelaers, Psychosocial safety climate as a moderator in role stressor-bullying relationships: A multilevel approach, Safety Science 164 (2023) 106165. DOI: https://doi.org/10.1016/j.ssci.2023.106165
• [28] A. Kjærgaard, E.M. Rudolf, J. Palmqvist, M.E. Jakobsen, J.Z.N. Ajslev, The psychosocial hierarchy of controls: effectively reducing psychosocial hazards at work, American Journal of Industrial Medicine 68/3 (2025) 250-263. DOI: https://doi.org/10.1002/ajim.23694
• [29] I. Bolis, T.F.A.C. Sigahi, S.N. Morioka, Raising psychosocial risks in real-world work environments: A proposal for a detailed and quick questionnaire with direct application by workers, Safety Science 173 (2024) 106439. DOI: https://doi.org/10.1016/j.ssci.2024.106439
• [30] W.A. Tol, P.T.D. Le, S.L. Harrison, A. Galappatti, J. Annan, F.K. Baingana, T.S. Betancourt, C. Bizouerne, J. Eaton, M. Engels, Z. Hijazi, R.R. Horn, M.J.D. Jordns, B.A Kohrt, P. Koyiet, C. Panter-Brick, M. Pluess, A. Rahman, D. Silove, M. Tomlinson, J.M. Uribe-Restrepo, P. Ventevogel, I. Weissbecker, A. Ager, M. van Ommeren, Mental health and psychosocial support in humanitarian settings: research priorities for 2021–30, The Lancet Global Health 11/6 (2023) e969-e975. DOI: https://doi.org/10.1016/S2214-109X(23)00128-6
• [31] A.P. Bochkovskуi, Elaboration of stochastic models to comprehensive evaluation of occupational risks in complex dynamic systems, Journal of Achievements in Materials and Manufacturing Engineering 104/1 (2021) 31-41. DOI: https://doi.org/10.5604/01.3001.0014.8484
• [32] A. Ruud, Convex Optimization: Theory, Methods and Applications, Nova Science Publishers, Hauppauge NY, USA, 2019.
• [33] N. Butto, Four Phases of Life and Four Stages of Stress: A New Stress Theory and Health Concept, International Journal of Psychiatry Research 2/6 (2019) 1-7. DOI: https://doi.org/10.33425/2641-4317.1035
• [34] M.S.C. Sep, K. Veenman, C. Vinkers, STRESS-EU consortium, Consortium members, M.S.C. Sep, K. Veenman, P.C. Habets, V. Bonapersona, P. Bakvis, U. Bentele, E. Binder, S.J.T. Branje, T. Brückl, S. Cornelisse, P. Dickinson, B. M. Elzinga, A.W.M. Evers, G. Fernández, E. Geuze, C.A. Hartman, E.J. Hermans, D. Hernaus, M. Joëls, R. Kaldewaij, W.H.J. Meeus, M. Meier, H. van Middendorp, S.A. Nelemans, N. Oei, T. Oldehinkel, J. van Peer, J. Pruessner, C. Quaedflieg, K. Roelofs, S.R. de Rooij, L. Schwabe, T. Smeets, V. Spoormaker, M.S. Tollenaar, R. Tutunji, A. Tyborowska, C. Vinkers, The STRESS-EU database: A European resource of human acute stress studies for the worldwide research community, Neuroscience Applied 3 (2024) 104063. DOI: https://doi.org/10.1016/j.nsa.2024.104063
• [35] C.-C. Chu, C.-Y. Chou, Hybrid work stressors and psychological withdrawal behavior: A moderated mediation model of emotional exhaustion and proactive personality, Journal of Vocational Behavior 155 (2024) 104053. DOI: https://doi.org/10.1016/j.jvb.2024.104053
• [36] S. Thuillard, L. Audergon, T. Kotalova, A. Sonderegger, J. Sauer, Human and machine-induced social stress in complex work environments: Effects on performance and subjective state, Applied Ergonomics 115 (2024) 104179. DOI: https://doi.org/10.1016/j.apergo.2023.104179
• [37] A.P. Bochkovskyi, N.Yu. Sapozhnikova, Development of system of automated occupational health and safety management in enterprises, Journal of Achievements in Materials and Manufacturing Engineering 107/1 (2021) 28-41. DOI: https://doi.org/10.5604/01.3001.0015.2454
• [38] A.P. Bochkovskyi, N.Yu. Sapozhnikova, Development of system of automated protection of employees from covid-19 and other infections at the enterprise, Journal of Achievements in Materials and Manufacturing Engineering 112/2 (2022) 70-85. DOI: https://doi.org/10.5604/01.3001.0016.0705
• [39] M.P. Claramonte, S.N. Caballero, D.E. Tortosa, M.D. Contreras-Aguilar, J.J. C. Madrigal, J.J. H. Morante, A.N. Carrillo, M.P. Rios, E. Chicharro-Luna, The stress experienced in an emergency medical service (EMS): A descriptive study, International Emergency Nursing 74 (2024) 101450. DOI: https://doi.org/10.1016/j.ienj.2024.101450
• [40] C. Huang, J. Zou, H. Ma, Y. Zhong, Role stress, occupational burnout and depression among emergency nurses: A cross-sectional study, International Emergency Nursing 72 (2024), 101387. DOI: https://doi.org/10.1016/j.ienj.2023.101387
• [41] N.K. Singh, S. Chung, A.-Y. Chang, J. Wang, D.A. Hall, A non-invasive wearable stress patch for real-time cortisol monitoring using a pseudoknot-assisted aptamer, Biosensors and Bioelectronics 227 (2023) 115097. DOI: https://doi.org/10.1016/j.bios.2023.115097
• [42] Y. Chen, Y. Liu, C. Lu, P. Chai, S. Li, Y. Zou, Research on work-stress recognition for deep ground miners based on depth-separable convolutional neural network, Journal of Loss Prevention in the Process Industries 91 (2024) 105410. DOI: https://doi.org/10.1016/j.jlp.2024.105410

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2026).