Mental Health Causation in the Construction Industry: A Systematic Review Employing a Psychological Safety Climate Model
Abstract
:1. Introduction
2. Materials and Methods
- “mental health”, “construction industry*”; “psychological health” OR “psychosocial risk factors” OR “biopsychosocial risk” OR “work stress” OR “job stress” OR “workplace stress” OR “job burnout” OR “occupational stress” OR “occupational stressors” OR “job stressors” OR “organisational stressors” OR “burnout” OR “mental health” OR “mental illness” OR “psychological distress” OR “depression” OR “psychosocial working environment”
- AND “construction industry” OR “construction workers” OR “construction site” OR “construction project” OR “building industry”.
3. Results
3.1. Demographics
3.2. Psychological Safety Climate Domains
3.2.1. Organisation Participation
3.2.2. Organisation Communication
3.2.3. Management Priority
3.2.4. Management Commitment
4. Discussion
4.1. Conceptual Model and Research Agenda
4.2. The Research Gaps
- Existing literature highlights the significant influence of WHS conditions on the MH of construction workers. The construction industry’s historically poor WHS reputation contributes to a pervasive sense of fear among workers, regarding the existing risk of accidents and injuries [112], thereby acting as a stressor. However, there is a research gap in comprehensively understanding the intricate interrelation between WHS conditions and the MH of construction workers. Further research is required to delve into this connection, exploring how specific aspects of workplace safety impact workers’ mental well-being and how targeted interventions can effectively alleviate stress and improve MH outcomes in this industry. While several recent research studies have explored the implications of EEG in MH assessment, their analyses have predominantly focused on mental fatigue. However, with the construction industry witnessing rapid advances in information and communications technology (ICT) and digitalisation, there exists a research gap concerning the development of a robust data management system capable of supporting the decision-making process through the integration of machine learning algorithms [113]. Such a data management system could effectively leverage EEG data, along with other relevant factors, to enhance MH assessment methodologies in the construction sector, thereby contributing to improved worker well-being and overall project performance. Thus, further research in this area is essential to develop and validate the effectiveness of such a data-driven approach in MH evaluation and support within the construction industry.
- A research gap lies in the lack of investigations concerning the adoption process of ICT for identifying workers with MH issues within the construction industry. While ICT shows potential for enhancing mental health support, particularly in its capacity for identification, current research has not adequately explored the challenges and factors that influence the adoption of these technologies. The project-based nature of the construction industry, along with the prevalence of several small and medium-sized enterprises (SMEs) within it, further compounds this research gap, as the resistance of the construction sector to embracing new technologies, particularly among SMEs, remains a pertinent area of inquiry [114]. Thus, understanding and addressing the limitations faced by SMEs in the adoption process is crucial to effectively integrating ICT for MH-issue identification and support within the construction domain.
- Another research gap exists in the current literature concerning MH management, with a predominant focus on the personal level of MH management while comparatively less attention is given to exploring organisational approaches and solutions. Established WHS models, such as the Swiss Cheese model or the ConAC, highlight the chain of events leading to accidents, whereas the personal level represents the final link [99]. However, in the context of burnouts within construction organisations, which can be considered as MH accidents, there is no comprehensive model that identifies critical layers and factors within construction organisations to effectively mitigate the likelihood of burnouts. Further research is required to develop and validate such a burnout model specific to construction settings, which could facilitate targeted interventions and strategies for promoting mental well-being and reducing the incidence of burnouts among construction workers.
- The very latest research, published in highly rated scientific journals, underpins the importance of leading indicator development to proactively predict and mitigate deleterious circumstances that could lead to an accident or incident on site [40,41]. Such work could also tentatively be used as a basis for developing MH leading indicators, as the processes and theories underpinning health, safety and well-being are aligned.
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Hon, C.K.; Sun, C.; Way, K.A.; Jimmieson, N.L.; Xia, B.; Biggs, H.C. Psychosocial hazards affecting mental health in the construction industry: A qualitative study in Australia. Eng. Constr. Archit. Manag. 2023. [Google Scholar] [CrossRef]
- Welton, M.; Shen, Y.; Ebell, M.; DeJoy, D.; Robb, S.W. Construction employment mortality among Mexican immigrants in the South Eastern United States, 2003–2013. Int. J. Migr. Health Soc. Care 2020, 16, 349–358. [Google Scholar] [CrossRef]
- Chan, A.P.; Nwaogu, J.M.; Naslund, J.A. Mental ill-health risk factors in the construction industry: Systematic review. J. Constr. Eng. Manag. 2020, 146, 04020004. [Google Scholar] [CrossRef] [PubMed]
- Liversedge, B. Mental health in construction- building the next storey. Safety Management Magazine, 8 February 2023. [Google Scholar]
- Roche, A.M.; Fischer, J.; Pidd, K.; Lee, N.; Battams, S.; Nicholas, R. Workplace Mental Illness and Substance Use Disorders in Male-Dominated Industries: A Systematic Literature Review. National Centre for Education and Training on Addiction (NCETA). 2012. Available online: https://researchnow.flinders.edu.au/en/publications/workplace-mental-illness-and-substance-use-disorders-in-male-domi (accessed on 25 May 2023).
- Lingard, H. Occupational health and safety in the construction industry. Constr. Manag. Econ. 2013, 31, 505–514. [Google Scholar] [CrossRef]
- Hulls, P.M.; de Vocht, F.; Martin, R.M.; Langford, R.M. “We are our own worst enemy”: A qualitative exploration of work-related stress in the construction industry. Int. J. Workplace Health Manag. 2022, 15, 609–622. [Google Scholar] [CrossRef]
- Rajgopal, T. Mental well-being at the workplace. Indian J. Occup. Environ. Med. 2010, 14, 63. [Google Scholar] [CrossRef]
- Hall, G.B.; Dollard, M.F.; Coward, J. Psychosocial safety climate: Development of the PSC-12. Int. J. Stress Manag. 2010, 17, 353. [Google Scholar] [CrossRef]
- World Health Organization. Mental Health Strengthening Our Response. Available online: https://www.who.int/news-room/fact-sheets/detail/mental-health-strengthening-our-response (accessed on 25 May 2023).
- Beyondblue PricewaterhouseCoopers Australia. Creating a Mentally Healthy Workplace: Return on Investment Analysis; Beyondblue PricewaterhouseCoopers Australia: Sydney, Australia, 2014. [Google Scholar]
- National Health Services. Every Mind Matters. Available online: https://www.nhs.uk/every-mind-matters/ (accessed on 25 May 2022).
- Bush, P.W.; Drake, R.E.; Xie, H.; McHugo, G.J.; Haslett, W.R. The long-term impact of employment on mental health service use and costs for persons with severe mental illness. Psychiatr. Serv. 2009, 60, 1024–1031. [Google Scholar] [CrossRef]
- Beswick, J.; Rogers, K.; Corbett, E.; Binch, S.; Jackson, K. An analysis of the prevalence and distribution of stress in the construction industry. Health Saf. Exec. 2007, 1–81. [Google Scholar]
- Riggall, M.; Skues, J.; Wise, L. Apprenticeship bullying in the building and construction industry. Educ. Train. 2017, 59, 502–515. [Google Scholar] [CrossRef]
- Ross, V.; Mathieu, S.L.; Wardhani, R.; Gullestrup, J.; Kõlves, K. Factors associated with workplace bullying and the mental health of construction industry apprentices: A mixed methods study. Front. Psychiatry 2021, 12, 629262. [Google Scholar] [CrossRef] [PubMed]
- Pidd, K.; Duraisingam, V.; Roche, A.; Trifonoff, A. Young construction workers: Substance use, mental health, and workplace psychosocial factors. Adv. Dual Diagn. 2017, 10, 155–168. [Google Scholar] [CrossRef]
- Berry, J.G.; Pidd, K.; Roche, A.M.; Harrison, J.E. Prevalence and patterns of alcohol use in the Australian workforce: Findings from the 2001 National Drug Strategy Household Survey. Addiction 2007, 102, 1399–1410. [Google Scholar] [CrossRef] [PubMed]
- Roche, A.M.; Pidd, K.; Bywood, P.; Freeman, T. Methamphetamine use among Australian workers and its implications for prevention. Drug Alcohol Rev. 2008, 27, 334–341. [Google Scholar] [CrossRef]
- Burki, T. Mental health in the construction industry. Lancet Psychiatry 2018, 5, 303. [Google Scholar] [CrossRef]
- Sun, C.; Hon, C.K.H.; Way, K.A.; Jimmieson, N.L.; Xia, B. The relationship between psychosocial hazards and mental health in the construction industry: A meta-analysis. Saf. Sci. 2022, 145, 105485. [Google Scholar] [CrossRef]
- Duckworth, J.; Hasan, A.; Kamardeen, I. Mental health challenges of manual and trade workers in the construction industry: A systematic review of causes, effects and interventions. Eng. Constr. Archit. Manag. 2022. [Google Scholar] [CrossRef]
- Oni, O.Z.; Olanrewaju, A.; Khor, S.C.; Akinbile, B.F. A comparative analysis of construction workers’ mental health before and during COVID-19 pandemic in Nigeria. Front. Eng. Built Environ. 2023, 3, 63–75. [Google Scholar] [CrossRef]
- Palaniappan, K.; Rajaraman, N.; Ghosh, S. Effectiveness of peer support to reduce depression, anxiety and stress among migrant construction workers in Singapore. Eng. Constr. Archit. Manag. 2022. [Google Scholar] [CrossRef]
- Xie, L.; Luo, Z.; Xia, B. Influence of psychosocial safety climate on construction workers’ intent to stay, taking job satisfaction as the intermediary. Eng. Constr. Archit. Manag. 2022. [Google Scholar] [CrossRef]
- Nwaogu, J.M.; Chan, A.P.; Hon, C.K.; Darko, A. Review of global mental health research in the construction industry: A science mapping approach. Eng. Constr. Archit. Manag. 2020, 27, 385–410. [Google Scholar] [CrossRef]
- Bayramova, A.; Edwards, D.J.; Roberts, C. The role of blockchain technology in augmenting supply chain resilience to cybercrime. Buildings 2021, 11, 283. [Google Scholar] [CrossRef]
- Edwards, D.J.; Akhtar, J.; Rillie, I.; Chileshe, N.; Lai, J.H.; Roberts, C.J.; Ejohwomu, O. Systematic analysis of driverless technologies. J. Eng. Des. Technol. 2022, 20, 1388–1411. [Google Scholar] [CrossRef]
- Posillico, J.; Edwards, D.; Roberts, C.; Shelbourn, M. Professional skills development: Foundational curriculum skills and competencies of UK construction management programmes. Educ. Train. 2023. [Google Scholar] [CrossRef]
- Roberts, C.; Edwards, D. Post-occupancy evaluation: Identifying and mitigating implementation barriers to reduce environmental impact. J. Clean. Prod. 2022, 374, 133957. [Google Scholar] [CrossRef]
- Chamberlain, D.A.; Edwards, D.; Lai, J.; Thwala, W.D. Mega event management of formula one grand prix: An analysis of literature. Facilities 2019, 37, 1166–1184. [Google Scholar] [CrossRef]
- Pawson, R.; Greenhalgh, T.; Harvey, G.; Walshe, K. Realist review-a new method of systematic review designed for complex policy interventions. J. Health Serv. Res. Policy 2005, 10, 21–34. [Google Scholar] [CrossRef]
- Al-Saeed, Y.; Edwards, D.J.; Scaysbrook, S. Automating construction manufacturing procedures using BIM digital objects (BDOs) Case study of knowledge transfer partnership project in UK. Constr. Innov. 2020, 20, 345–377. [Google Scholar] [CrossRef]
- Taylor, K.; Edwards, D.J.; Lai, J.H.; Rillie, I.; Thwala, W.D.; Shelbourn, M. Converting commercial and industrial property into rented residential accommodation: Development of a decision support tool. Facilities 2023, 41, 1–29. [Google Scholar] [CrossRef]
- Lingard, H.; Turner, M. Improving the health of male, blue collar construction workers: A social ecological perspective. Constr. Manag. Econ. 2015, 33, 18–34. [Google Scholar] [CrossRef]
- Law, R.; Dollard, M.F.; Tuckey, M.R.; Dormann, C. Psychosocial safety climate as a lead indicator of workplace bullying and harassment, job resources, psychological health and employee engagement. Accid. Anal. Prev. 2011, 43, 1782–1793. [Google Scholar] [CrossRef]
- Zadow, A.J.; Dollard, M.F.; Mclinton, S.S.; Lawrence, P.; Tuckey, M.R. Psychosocial safety climate, emotional exhaustion, and work injuries in healthcare workplaces. Stress Health 2017, 33, 558–569. [Google Scholar] [CrossRef] [PubMed]
- Dollard, M.F.; Tuckey, M.R.; Dormann, C. Psychosocial safety climate moderates the job demand–resource interaction in predicting workgroup distress. Accid. Anal. Prev. 2012, 45, 694–704. [Google Scholar] [CrossRef] [PubMed]
- Idris, M.A.; Dollard, M.F.; Coward, J.; Dormann, C. Psychosocial safety climate: Conceptual distinctiveness and effect on job demands and worker psychological health. Saf. Sci. 2012, 50, 19–28. [Google Scholar] [CrossRef]
- Bayramova, A.; Edwards, D.J.; Roberts, C.; Rillie, I. Constructs of leading indicators: A synthesis of safety literature. J. Saf. Res. 2023, 85, 469–484. [Google Scholar] [CrossRef] [PubMed]
- Bayramova, A.; Edwards, D.J.; Roberts, C.; Rillie, I. Enhanced safety in complex socio-technical systems via safety-in-cohesion. Saf. Sci. 2023, 164, 106176. [Google Scholar] [CrossRef]
- Watson, R.T.; Webster, J. Analysing the past to prepare for the future: Writing a literature review a roadmap for release 2.0. J. Decis. Syst. 2020, 29, 129–147. [Google Scholar] [CrossRef]
- Posillico, J.J.; Edwards, D.J.; Roberts, C.; Shelbourn, M. A conceptual construction management curriculum model grounded in scientometric analysis. Eng. Constr. Archit. Manag. 2022. [Google Scholar] [CrossRef]
- Chen, J.; Taylor, J.E.; Comu, S. Assessing task mental workload in construction projects: A novel electroencephalography approach. J. Constr. Eng. Manag. 2017, 143, 04017053. [Google Scholar] [CrossRef]
- Jebelli, H.; Hwang, S.; Lee, S. EEG-based workers’ stress recognition at construction sites. Autom. Constr. 2018, 93, 315–324. [Google Scholar] [CrossRef]
- Jebelli, H.; Hwang, S.; Lee, S. EEG signal-processing framework to obtain high-quality brain waves from an off-the-shelf wearable EEG device. J. Comput. Civ. Eng. 2018, 32, 04017070. [Google Scholar] [CrossRef]
- Xing, X.; Zhong, B.; Luo, H.; Rose, T.; Li, J.; Antwi-Afari, M.F. Effects of physical fatigue on the induction of mental fatigue of construction workers: A pilot study based on a neurophysiological approach. Autom. Constr. 2020, 120, 103381. [Google Scholar] [CrossRef]
- Jebelli, H.; Choi, B.; Lee, S. Application of wearable biosensors to construction sites. I: Assessing workers’ stress. J. Constr. Eng. Manag. 2019, 145, 04019079. [Google Scholar] [CrossRef]
- Li, J.; Li, H.; Wang, H.; Umer, W.; Fu, H.; Xing, X. Evaluating the impact of mental fatigue on construction equipment operators’ ability to detect hazards using wearable eye-tracking technology. Autom. Constr. 2019, 105, 102835. [Google Scholar] [CrossRef]
- Powell, R.; Copping, A. Sleep deprivation and its consequences in construction workers. J. Constr. Eng. Manag. 2010, 136, 1086–1092. [Google Scholar] [CrossRef]
- Newman, C.; Edwards, D.; Martek, I.; Lai, J.; Thwala, W.D.; Rillie, I. Industry 4.0 deployment in the construction industry: A bibliometric literature review and UK-based case study. Smart Sustain. Built Environ. 2021, 10, 557–580. [Google Scholar] [CrossRef]
- Elghaish, F.; Matarneh, S.T.; Edwards, D.J.; Rahimian, F.P.; El-Gohary, H.; Ejohwomu, O. Applications of Industry 4.0 digital technologies towards a construction circular economy: Gap analysis and conceptual framework. Constr. Innov. 2022, 22, 647–670. [Google Scholar] [CrossRef]
- Chong, D.; Chen, L.; Peng, Y.; Yu, A. Occupational noise-related perception and personal protection behavior among Chinese construction workers. Saf. Sci. 2022, 147, 105629. [Google Scholar] [CrossRef]
- Johari, S.; Jha, K.N. How the aptitude of workers affects construction labor productivity. J. Manag. Eng. 2020, 36, 04020055. [Google Scholar] [CrossRef]
- Mubarak, N.; Khan, J.; Khan, A.K. Psychological distress and project success: The moderating role of employees’ resilience and mindfulness. Int. J. Proj. Manag. 2022, 40, 566–576. [Google Scholar] [CrossRef]
- Kurtzer, D.; Blackmore, N.; Farrugia, N.; Chileshe, N. Productivity enablers and inhibiting health and wellbeing practices of South Australian construction site-based workers: A qualitative study. Int. J. Constr. Manag. 2020, 20, 882–899. [Google Scholar] [CrossRef]
- Gullestrup, J.; Lequertier, B.; Martin, G. MATES in construction: Impact of a multimodal, community-based program for suicide prevention in the construction industry. Int. J. Environ. Res. Public Health 2011, 8, 4180–4196. [Google Scholar] [CrossRef] [PubMed]
- Lingard, H.; Turner, M. Promoting construction workers’ health: A multi-level system perspective. Constr. Manag. Econ. 2017, 35, 239–253. [Google Scholar] [CrossRef]
- Milner, A.; Law, P.; Mann, C.; Cooper, T.; Witt, K.; LaMontagne, A. A smart-phone intervention to address mental health stigma in the construction industry: A two-arm randomised controlled trial. SSM-Popul. Health 2018, 4, 164–168. [Google Scholar] [CrossRef]
- Milner, A.; Witt, K.; Burnside, L.; Wilson, C.; LaMontagne, A.D. Contact & connect—An intervention to reduce depression stigma and symptoms in construction workers: Protocol for a randomised controlled trial. BMC Public Health 2015, 15, 1062. [Google Scholar]
- Bowen, P.; Edwards, P.; Lingard, H.; Cattell, K. Occupational stress and job demand, control and support factors among construction project consultants. Int. J. Proj. Manag. 2014, 32, 1273–1284. [Google Scholar] [CrossRef]
- Elo, A.-L.; Ervasti, J.; Kuosma, E.; Mattila-Holappa, P. Effect of a leadership intervention on subordinate well-being. J. Manag. Dev. 2014, 33, 182–195. [Google Scholar] [CrossRef]
- Leung, M.-y.; Bowen, P.; Liang, Q.; Famakin, I. Development of a job-stress model for construction professionals in South Africa and Hong Kong. J. Constr. Eng. Manag. 2015, 141, 04014077. [Google Scholar] [CrossRef]
- Wang, Y.; Han, Q.; De Vries, B.; Zuo, J. How the public reacts to social impacts in construction projects? A structural equation modeling study. Int. J. Proj. Manag. 2016, 34, 1433–1448. [Google Scholar] [CrossRef]
- Kamardeen, I.; Sunindijo, R.Y. Personal characteristics moderate work stress in construction professionals. J. Constr. Eng. Manag. 2017, 143, 04017072. [Google Scholar] [CrossRef]
- Love, P.E.; Edwards, D.J.; Irani, Z. Work stress, support, and mental health in construction. J. Constr. Eng. Manag. 2010, 136, 650–658. [Google Scholar] [CrossRef]
- Chakraborty, T.; Das, S.K.; Pathak, V.; Mukhopadhyay, S. Occupational stress, musculoskeletal disorders and other factors affecting the quality of life in Indian construction workers. Int. J. Constr. Manag. 2018, 18, 144–150. [Google Scholar] [CrossRef]
- Abhijith, R.; Deepika, C.; Mirfath, P.; Menon, S. Psychosocial and Occupational Hazards in Kerala Construction Industry. In Lecture Notes in Civil Engineering, Proceedings of the SECON’19: Structural Engineering and Construction Management 3; Springer: Berlin/Heidelberg, Germany, 2020; pp. 655–664. [Google Scholar]
- Boschman, J.; Van der Molen, H.; Sluiter, J.; Frings-Dresen, M. Psychosocial work environment and mental health among construction workers. Appl. Ergon. 2013, 44, 748–755. [Google Scholar] [CrossRef] [PubMed]
- Boschman, J.; Van Der Molen, H.; Frings-Dresen, M.; Sluiter, J. The impact of common mental disorders on work ability in mentally and physically demanding construction work. Int. Arch. Occup. Environ. Health 2014, 87, 51–59. [Google Scholar] [CrossRef]
- Langdon, R.R.; Sawang, S. Construction workers’ well-being: What leads to depression, anxiety, and stress? J. Constr. Eng. Manag. 2018, 144, 04017100. [Google Scholar] [CrossRef]
- Sobeih, T.M.; Salem, O.; Daraiseh, N.; Genaidy, A.; Shell, R. Psychosocial factors and musculoskeletal disorders in the construction industry: A systematic review. Theor. Issues Ergon. Sci. 2006, 7, 329–344. [Google Scholar] [CrossRef]
- Cox, T.; Griffiths, A.; Barlowe, C.; Randall, R.; Thomson, L.; Rial-Gonzalez, E. Organisational Interventions for Work Stress A Risk Management Approach. HSE Contract Research Report. 2000. Available online: https://www.hse.gov.uk/research/rrpdf/CRR287/2000.pdf (accessed on 25 May 2022).
- Gershon, R.R.; Karkashian, C.D.; Grosch, J.W.; Murphy, L.R.; Escamilla-Cejudo, A.; Flanagan, P.A.; Bernacki, E.; Kasting, C.; Martin, L. Hospital safety climate and its relationship with safe work practices and workplace exposure incidents. Am. J. Infect. Control 2000, 28, 211–221. [Google Scholar] [CrossRef]
- Liu, Y.; Habibnezhad, M.; Jebelli, H. Brainwave-driven human-robot collaboration in construction. Autom. Constr. 2021, 124, 103556. [Google Scholar] [CrossRef]
- Adeyemi, B.S.; Aigbavboa, C.O. An exploratory factor analysis for conflict resolution methods among construction professionals. Buildings 2022, 12, 854. [Google Scholar] [CrossRef]
- Lingard, H.; Zhang, R.P.; LaBond, C.; Clarke, J.; Doan, T. Situated Learning: How Interactions with Supervisors Shape Construction Apprentices’ Safety Learning and Practice. J. Constr. Eng. Manag. 2022, 148, 04022107. [Google Scholar] [CrossRef]
- Pousette, A.; Törner, M. Effects of systematic work preparation meetings on safety climate and psychosocial conditions in the construction industry. Constr. Manag. Econ. 2016, 34, 355–365. [Google Scholar] [CrossRef]
- Zika-Viktorsson, A.; Hovmark, S.; Nordqvist, S. Psychosocial aspects of project work: A comparison between product development and construction projects. Int. J. Proj. Manag. 2003, 21, 563–569. [Google Scholar] [CrossRef]
- Hampton, P.; Chinyio, E.A.; Riva, S. Framing stress and associated behaviours at work: An ethnography study in the United Kingdom. Eng. Constr. Archit. Manag. 2019, 26, 2566–2580. [Google Scholar] [CrossRef]
- Kazaz, A.; Ulubeyli, S. Drivers of productivity among construction workers: A study in a developing country. Build. Environ. 2007, 42, 2132–2140. [Google Scholar] [CrossRef]
- Tijani, B.; Osei-Kyei, R.; Feng, Y. A review of work-life balance in the construction industry. Int. J. Constr. Manag. 2022, 22, 2671–2686. [Google Scholar] [CrossRef]
- Zika-Viktorsson, A.; Sundström, P.; Engwall, M. Project overload: An exploratory study of work and management in multi-project settings. Int. J. Proj. Manag. 2006, 24, 385–394. [Google Scholar] [CrossRef]
- McCabe, B.; Loughlin, C.; Munteanu, R.; Tucker, S.; Lam, A. Individual safety and health outcomes in the construction industry. Can. J. Civ. Eng. 2008, 35, 1455–1467. [Google Scholar] [CrossRef]
- Ahmad, R.; Nauman, S.; Malik, S.Z. Tyrannical leader, machiavellian follower, work withdrawal, and task performance: Missing links in construction projects. J. Constr. Eng. Manag. 2022, 148, 04022045. [Google Scholar] [CrossRef]
- Newaz, M.T.; Davis, P.; Jefferies, M.; Pillay, M. Examining the psychological contract as mediator between the safety behavior of supervisors and workers on construction sites. J. Constr. Eng. Manag. 2020, 146, 04019094. [Google Scholar] [CrossRef]
- Chih, Y.-Y.; Kiazad, K.; Zhou, L.; Capezio, A.; Li, M.; Restubog, S.L.D. Investigating employee turnover in the construction industry: A psychological contract perspective. J. Constr. Eng. Manag. 2016, 142, 04016006. [Google Scholar] [CrossRef]
- Ju, L.; Zhao, W.; Wu, C.; Li, H.; Ning, X. Abusive supervisors and employee work-to-family conflict in Chinese construction projects: How does family support help? Constr. Manag. Econ. 2020, 38, 1158–1178. [Google Scholar] [CrossRef]
- Li, K.; Griffin, M.A. Safety behaviors and job satisfaction during the pandemic: The mediating roles of uncertainty and managerial commitment. J. Saf. Res. 2022, 82, 166–175. [Google Scholar] [CrossRef] [PubMed]
- Liang, Y.; Baral, A.; Shahandashti, M.; Ashuri, B. Availability heuristic in construction workforce decision-making amid COVID-19 pandemic: Empirical evidence and mitigation strategy. J. Manag. Eng. 2022, 38, 04022046. [Google Scholar] [CrossRef]
- Chih, Y.-Y.; Kiazad, K.; Li, M.; Capezio, A.; Zhou, L.; Restubog, S.L.D. Broken promises: Implications for the job insecurity and job performance of Chinese construction workers. J. Constr. Eng. Manag. 2017, 143, 04016114. [Google Scholar] [CrossRef]
- Loosemore, M.; Lim, B.T.-H. Intra-organisational injustice in the construction industry. Eng. Constr. Archit. Manag. 2016, 23, 428–447. [Google Scholar] [CrossRef]
- Newaz, M.T.; Jefferies, M.; Davis, P.R.; Pillay, M. Managerial implications for construction practices as a consequence of using a psychological contract of safety. Eng. Constr. Archit. Manag. 2021, 28, 1134–1155. [Google Scholar] [CrossRef]
- Lingard, H.; Francis, V. Managing Work-Life Balance in Construction; Routledge: London, UK, 2009. [Google Scholar]
- Lingard, H.; Francis, V. The work-life experiences of office and site-based employees in the Australian construction industry. Constr. Manag. Econ. 2004, 22, 991–1002. [Google Scholar] [CrossRef]
- Haynes, N.S.; Love, P.E. Psychological adjustment and coping among construction project managers. Constr. Manag. Econ. 2004, 22, 129–140. [Google Scholar] [CrossRef]
- Carlson, D.; Kacmar, K.M.; Zivnuska, S.; Ferguson, M.; Whitten, D. Work-family enrichment and job performance: A constructive replication of affective events theory. J. Occup. Health Psychol. 2011, 16, 297. [Google Scholar] [CrossRef]
- Maslach, C.; Jackson, S.E. The measurement of experienced burnout. J. Organ. Behav. 1981, 2, 99–113. [Google Scholar] [CrossRef]
- Golizadeh, H.; Hon, C.K.; Drogemuller, R.; Hosseini, M.R. Digital engineering potential in addressing causes of construction accidents. Autom. Constr. 2018, 95, 284–295. [Google Scholar] [CrossRef]
- Hwang, S.; Jebelli, H.; Choi, B.; Choi, M.; Lee, S. Measuring workers’ emotional state during construction tasks using wearable EEG. J. Constr. Eng. Manag. 2018, 144, 04018050. [Google Scholar] [CrossRef]
- Penney, L.M.; Spector, P.E. Job stress, incivility, and counterproductive work behavior (CWB): The moderating role of negative affectivity. J. Organ. Behav. 2005, 26, 777–796. [Google Scholar] [CrossRef]
- Chen, Y.; McCabe, B.; Hyatt, D. Relationship between individual resilience, interpersonal conflicts at work, and safety outcomes of construction workers. J. Constr. Eng. Manag. 2017, 143, 04017042. [Google Scholar] [CrossRef]
- Ng, S.T.; Tang, Z. Labour-intensive construction sub-contractors: Their critical success factors. Int. J. Proj. Manag. 2010, 28, 732–740. [Google Scholar] [CrossRef]
- Marzouk, M.M.; El Kherbawy, A.A.; Khalifa, M. Factors influencing sub-contractors selection in construction projects. Hbrc J. 2013, 9, 150–158. [Google Scholar] [CrossRef]
- Sauter, S.L.; Hurrell, J.J.; Cooper, C.L. Job Control and Worker Health; Wiley: Hoboken, NJ, USA, 1989. [Google Scholar]
- Schieman, S.; Reid, S. Job authority and health: Unraveling the competing suppression and explanatory influences. Soc. Sci. Med. 2009, 69, 1616–1624. [Google Scholar] [CrossRef] [PubMed]
- Janssen, P.P.; Bakker, A.B.; de Jong, A. A test and refinement of the Demand–Control–Support Model in the construction industry. Int. J. Stress Manag. 2001, 8, 315–332. [Google Scholar] [CrossRef]
- Johnson, J.V.; Hall, E.M.; Theorell, T. Combined effects of job strain and social isolation on cardiovascular disease morbidity and mortality in a random sample of the Swedish male working population. Scand. J. Work Environ. Health 1989, 15, 271–279. [Google Scholar] [CrossRef]
- Michie, S. Causes and management of stress at work. Occup. Environ. Med. 2002, 59, 67–72. [Google Scholar] [CrossRef]
- Adane, M.M.; Gelaye, K.A.; Beyera, G.K.; Sharma, H.R.; Yalew, W.W. Occupational injuries among building construction workers in Gondar City, Ethiopia. Occup. Med. Health Aff. 2013, 1, 5. [Google Scholar] [CrossRef]
- Peng, L.; Chan, A.H. Adjusting work conditions to meet the declined health and functional capacity of older construction workers in Hong Kong. Saf. Sci. 2020, 127, 104711. [Google Scholar] [CrossRef]
- Golzad, H.; Saeed, B.; Hon, C.; Drogemuller, R. BIM and Construction Health and Safety—Uncovering, Adoption and Implementation; Routledge: London, UK, 2023; p. 166. [Google Scholar] [CrossRef]
- Bortey, L.; Edwards, D.J.; Roberts, C.; Rillie, I. A Review of Safety Risk Theories and Models and the Development of a Digital Highway Construction Safety Risk Model. Digital 2022, 2, 206–223. [Google Scholar] [CrossRef]
- Hosseini, M.; Banihashemi, S.; Chileshe, N.; Namzadi, M.O.; Udaeja, C.; Rameezdeen, R.; McCuen, T. BIM adoption within Australian Small and Medium-sized Enterprises (SMEs): An innovation diffusion model. Constr. Econ. Build. 2016, 16, 71–86. [Google Scholar] [CrossRef]
Source Title | No. of Articles (f) | Percentage (%) |
---|---|---|
Journal of Construction Engineering and Management | 21 | 29.58 |
Automation in Construction | 9 | 12.68 |
Construction Management and Economics | 8 | 11.27 |
Journal of Management in Engineering | 9 | 12.68 |
Engineering, Construction and Architectural Management | 6 | 8.45 |
International Journal of Project Management | 6 | 8.45 |
Safety Science | 4 | 5.63 |
International Journal of Construction Management | 3 | 4.23 |
Building and Environment | 3 | 4.23 |
Safety Research | 1 | 1.41 |
Applied Economics | 1 | 1.41 |
Canadian Journal of Civil Engineering | 1 | 1.41 |
Human Factors and Ergonomics in Manufacturing | 1 | 1.41 |
International Journal of Construction Education and Research | 1 | 1.41 |
Journal of Computing in Civil Engineering | 1 | 1.41 |
Journal of Financial Management of Property and Construction | 1 | 1.41 |
Journal of Management Development | 1 | 1.41 |
Buildings | 1 | 1.41 |
Author | Assessment Method | Major Causative Factor | Intervention |
---|---|---|---|
[44] | EEG | Inappropriate task allocation | EEG can be useful in estimating task mental workload |
[45] | EEG | - | EEG can be useful in understanding workers’ psychosocial conditions |
[46] | EEG | Stress | Learning algorithms can be used to recognise workers’ stress from EEG output |
[49] | EEG | Pre-service fatigue | Screening targets can be identified by pre-service EEG test |
[47] | EEG | Physical fatigue | Stress management programme |
[49] | Eye-tracking | Physical fatigue | Eye-tracking is effective in quantifying machine operator mental fatigue |
[50] | Wearable sensor | Sleep deprivation | Actimetry sensor can be used in investigating sleep and mental efficiency |
[48] | Wearable biosensor | Inherent stressful job | Early detection of occupational stressors can enhance performance and safety |
[57] | Questionnaire | - | Early intervention program/training/suicide hotline |
[61] | Questionnaire | Economic and social issues/unhealthy lifestyle | Organisational and personal stress-management intervention |
[62] | Intervention Assessment Surveys | - | Personal growth-orientated programmes contribute to MH |
[63] | Survey | Lack of proper equipment/working quickly | On-job training/stress-reduction programs decrease accidents |
[64] | Questionnaire | Lack of proper equipment and difficult working conditions | Artificial oxygen supply for tunnel workers increases physical performance but causes anxiety |
[56] | Interviews | Prevalent unhealthy lifestyle | Awareness programs, particularly for ageing workforce |
[65] | Questionnaire | Marital status/gender | Family friendly employment policy could moderate stress, resulting in cost saving |
[66] | Questionnaire | Emotional intelligence | Emotional intelligence could be used to increase project performance |
[60] | Intervention Assessment | Self-stigma | Online anti-stigma program |
[59] | Intervention Assessment | Stigma in unemployed workers | Contacting and connecting programs |
[58] | Interview | Unhealthy lifestyle | Health promotion programme |
[66] | Questionnaire | High job demand | Self and work support |
[67] | Questionnaire | Long working hours, high demand | Regularly apprised about health and safety, proper PPE and equipment |
[68] | Questionnaire | Long working hours, stress, home/work conflict, organisation’s priority of productivity versus workers’ well-being | Over time, working and family conflict has a negative impact on work and family commitment |
[69] | Questionnaire | Lack of recovery after work, depression, post-traumatic stress, low participation in decision making, low social support | Psychosocial work factors should be assessed job-specifically |
[70] | Questionnaire | Common mental disorders result in low work ability | The use of job-specific questions on work ability to identify preventive actions |
[71] | Questionnaire | Lack of personal/family time, cost of living, self-stigma | Education on self-stigma, and replacement with positive strategies |
[55] | Questionnaire | Employees’ lack of resilience and mindfulness | Theoretical directions to minimise psychological distress among project employees |
[53] | Questionnaire | Stressful/unhealthy work environment | The noise sensitivity of the workers has a major impact on their risk perception |
Author | Assessment Method | Major Causative Factor | Intervention |
---|---|---|---|
[78] | Questionnaire | Workers’ perceptions of influence at work, of workload and of cooperation | Education, support |
[80] | EEG | Physical status, interpersonal relationships, emotional well-being | Job training, psychological services, leadership organisational changes |
[79] | Questionnaire | Organisation/leadership structures, objects/outcomes nature | Exchange of ideas, social processes, joint activities, team support |
[75] | EEG | Poor communication | Human-robot collaboration framework |
[63] | Questionnaire | High job demand Low job control and job support | Social gathering, job reallocation fair compensation policies |
[72] | Systematic review | Psychosocial and physical disorders e.g., musculoskeletal disorders | Education, training, connect and contact, and regulation |
[77] | Interview | Supervisor-apprentice communication | Context-based communications are more effective than classroom-based training |
[76] | Questionnaire | Poor communication | Construction professionals should collaborate with one another in order to solidify their relationship and enhance their performance within their professional bodies. |
Author | Assessment Method | Major Causative Factor | Intervention |
---|---|---|---|
[81] | Questionnaire | Socio-psychological factors | Monetary factors have more effects than psychological on performance |
[82] | Systematic review | Physical status, interpersonal relationships, emotional well-being | Job training, psychological services, leadership organisational changes |
[54] | General aptitude battery test and observation | Workers’ physical and mental aptitudes | Physical aptitude has more impact than mental aptitude on performance |
[83] | Questionnaire | Lack of recuperation opportunities, inadequate routines, scarce time resources, large number of simultaneous projects | - |
[84] | Questionnaire | Work pressure/leadership strategy | - |
[80] | Ethnographic observation | High job demand Low job control and job support | Social gathering, job reallocation, fair compensation policies |
[85] | Questionnaire | Unappreciative management | Workers’ personalities under tyrannical leadership induce work withdrawal behaviours. |
Article | Assessment Method | Major Causative Factor | Intervention |
---|---|---|---|
[61] | Questionnaire | Harassment/discrimination | Acknowledged and addressed by professional associations |
[88] | Questionnaire | Abusive management | Family support |
[91] | Questionnaires | Breaching psychological contract | Manage employees’ psychological contract expectations |
[87] | Questionnaires | Organisational injustice | Management practices that enhance fairness perception of workers |
[86] | Questionnaires | Breaching psychological contract | Managers’ commitment to psychological safety contract |
[92] | Questionnaires | Intra-organisational injustice | Organisational policies to reduce injustice in the construction industry |
[93] | Questionnaires | Psychological contract | Worker and supervisor good relationship |
[89] | Questionnaires | Job satisfaction and employment uncertainty during the pandemic | There is a direct link between the management commitment, higher psychological uncertainty, and safety compliance. |
[90] | Questionnaires | Decision-making uncertainty during the pandemic | Providing information on other options against the option with the easiest recalled instances has been proven effective |
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Share and Cite
Golzad, H.; Teimoory, A.; Mousavi, S.J.; Bayramova, A.; Edwards, D.J. Mental Health Causation in the Construction Industry: A Systematic Review Employing a Psychological Safety Climate Model. Buildings 2023, 13, 2442. https://doi.org/10.3390/buildings13102442
Golzad H, Teimoory A, Mousavi SJ, Bayramova A, Edwards DJ. Mental Health Causation in the Construction Industry: A Systematic Review Employing a Psychological Safety Climate Model. Buildings. 2023; 13(10):2442. https://doi.org/10.3390/buildings13102442
Chicago/Turabian StyleGolzad, Hamed, Atefeh Teimoory, Seyed Javid Mousavi, Aya Bayramova, and David J. Edwards. 2023. "Mental Health Causation in the Construction Industry: A Systematic Review Employing a Psychological Safety Climate Model" Buildings 13, no. 10: 2442. https://doi.org/10.3390/buildings13102442
APA StyleGolzad, H., Teimoory, A., Mousavi, S. J., Bayramova, A., & Edwards, D. J. (2023). Mental Health Causation in the Construction Industry: A Systematic Review Employing a Psychological Safety Climate Model. Buildings, 13(10), 2442. https://doi.org/10.3390/buildings13102442