Occupational Stressors and Safety Behaviour among Oil and Gas Workers in Kuwait: The Mediating Role of Mental Health and Fatigue
Abstract
:1. Introduction
1.1. Selected Occupational Stressors
1.2. Study Aim, Research Gap and Conceptual Model
1.3. Occupational Stressors—Safety Behaviour Relationship
1.4. Mental Health as a Mediating Variable
1.4.1. Occupational Stressors—Mental Health Relationship
1.4.2. Mental Health—Safety Behaviour Relationship
1.5. Fatigue as a Mediating Variable
1.5.1. Occupational Stressors—Fatigue Relationship
1.5.2. Fatigue—Safety Behaviour Relationship
2. Materials and Methods
2.1. Study Setting and Participants
2.2. Questionnaire Design and Development
2.3. Data Analysis
- The independent variable (IV) predicts the mediator variable (M) (Path A);
- The IV predicts the dependent variable (DV) (Path C);
- The M predicts the DV (Path B);
- The indirect effect of the IV on the DV through the M is significant (Path A × B).
3. Results
3.1. Study Setting and Participants
3.2. Mediation Role of Anxiety
3.2.1. Anxiety Mediates the Relationship between Responsibilities towards Family and Safety Compliance
3.2.2. Anxiety Mediates the Relationship between Responsibilities towards Family and Safety Participation
3.2.3. Anxiety Mediates the Relationship between Living Environment and Safety Behaviour
3.3. Mediation Role of Depression
3.3.1. Depression Mediates the Relationship between Responsibilities towards Family and Safety Behaviour
3.3.2. Depression Mediates the Relationship between Living Environment and Safety Behaviour
3.4. Mediation Role of Physical Fatigue
3.4.1. Physical Fatigue Mediates the Relationship between Responsibilities towards Family and Safety Behaviour
3.4.2. Physical Fatigue Mediates the Relationship between Living Environment and Safety Behaviour
3.5. Mediation Role of Mental Fatigue
3.5.1. Mental Fatigue Mediates the Relationship between Responsibilities towards Family and Safety Behaviour
3.5.2. Mental Fatigue Mediates the Relationship between Living Environment and Safety Behaviour
4. Discussion
4.1. Direct Relationship between Occupational Stressors and Safety Behaviour
4.2. Mediating Role of Mental Health on the Relationship between Occupational Stressors and Safety Behaviour
4.3. Mediating Role of Fatigue on the Relationship between Occupational Stressors and Safety Behaviour
4.4. Theoretical Implications
4.5. Practical Implications
5. Conclusions
Limitations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Mearns, K.; Yule, S. The role of national culture in determining safety performance: Challenges for the global oil and gas industry. Saf. Sci. 2009, 47, 777–785. [Google Scholar] [CrossRef]
- Kim, B.-J.; Jung, S.-Y. The mediating role of job strain in the transformational leadership–safety behavior link: The buffering effect of self-efficacy on safety. Int. J. Environ. Res. Public Health 2019, 16, 1425. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kane, S. Iraq’s Oil Politics: Where Agreement Might Be Found. Vol. No. 64. 2010. US Institute of Peace, No. 64. Available online: http://www.usip.org/files/resources/iraq_oil_pw64.pdf (accessed on 26 May 2020).
- Leung, M.-y.; Chan, I.Y.S.; Cooper, C. Stress Management in the Construction Industry; John Wiley & Sons, Ltd.: Chichester, West Sussex, UK, 2015. [Google Scholar]
- Chen, W.Q.; Wong, T.W.; Yu, T.S. Mental health issues in Chinese offshore oil workers. Occup. Med. 2009, 59, 545–549. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Robbins, S.P. Organisational Behaviour, 10th ed.; Prentice-Hall Inc.: Hoboken, NJ, USA, 2007. [Google Scholar]
- Brešić, J.; Knežević, B.; Milošević, M.; Tomljanović, T.; Golubović, R.; Mustajbegović, J. Stress and work ability in oil industry workers. Arch. Ind. Hyg. Toxicol. 2007, 58, 399–405. [Google Scholar] [CrossRef] [PubMed]
- Sneddon, A.; Mearns, K.; Flin, R. Stress, fatigue, situation awareness and safety in offshore drilling crews. Saf. Sci. 2013, 56, 80–88. [Google Scholar] [CrossRef]
- Alroomi, A.S.; Mohamed, S. Remoteness, Mental Health and Safety Behaviour among Oil and Gas Workers. In Proceedings of the 10th International Conference on Construction in the 21st Century (CITC-10), Colombo, Sri Lanka, 2–4 July 2018; pp. 169–177. [Google Scholar]
- Bjerkan, A.M. Work and health: A comparison between Norwegian onshore and offshore employees. Work 2011, 40, 125–142. [Google Scholar] [CrossRef]
- Cooper, C.L.; Sutherland, V.J. Job stress, mental health, and accidents among offshore workers in the oil and gas extraction industries. J. Occup. Environ. Med. 1987, 29, 119–125. [Google Scholar]
- Chen, W.-Q.; Wong, T.-W.; Yu, T.-S. Reliability and validity of the Occupational Stress Scale for Chinese off-shore oil installation workers. Stress Health 2001, 17, 175–183. [Google Scholar] [CrossRef]
- Ghislieri, C.; Gatti, P.; Molino, M.; Cortese, C.G. Work–family conflict and enrichment in nurses: Between job demands, perceived organisational support and work–family backlash. J. Nurs. Manag. 2017, 25, 65–75. [Google Scholar] [CrossRef]
- Grandey, A.A.; Cropanzano, R. The conservation of resources model applied to work–family conflict and strain. J. Vocat. Behav. 1999, 54, 350–370. [Google Scholar] [CrossRef] [Green Version]
- Leung, M.-y.; Chan, Y.-S.; Yu, J. Integrated model for the stressors and stresses of construction project managers in Hong Kong. J. Constr. Eng. Manag. 2009, 135, 126–134. [Google Scholar] [CrossRef] [Green Version]
- Chen, M.-J.; Cunradi, C. Job stress, burnout and substance use among urban transit operators: The potential mediating role of coping behaviour. Work Stress 2008, 22, 327–340. [Google Scholar] [CrossRef]
- Greiner, B.A.; Krause, N.; Ragland, D.; Fisher, J.M. Occupational stressors and hypertension: A multi-method study using observer-based job analysis and self-reports in urban transit operators. Soc. Sci. Med. 2004, 59, 1081–1094. [Google Scholar] [CrossRef] [PubMed]
- Clarke, S. The effect of challenge and hindrance stressors on safety behavior and safety outcomes: A meta-analysis. J. Occup. Health Psychol. 2012, 17, 387. [Google Scholar] [CrossRef]
- Parkes, K.R. Mental health in the oil industry: A comparative study of onshore and offshore employees. Psychol. Med. 1992, 22, 997–1009. [Google Scholar] [CrossRef]
- Hofmann, D.A.; Stetzer, A. A cross-level investigation of factors influencing unsafe behaviors and accidents. Pers. Psychol. 1996, 49, 307–339. [Google Scholar] [CrossRef]
- Chu, F.; Guo, M.; Liu, S.; Chen, S. Work-family conflict, personality, and safety behaviors among high-speed railway drivers. J. Transp. Saf. Secur. 2020, 12, 1147–1163. [Google Scholar] [CrossRef]
- Johnson, R.C.; Eatough, E.M.; Hammer, L.B.; Truxilllo, D. Home is where the mind is: Family interference with work and safety performance in two high risk industries. J. Vocat. Behav. 2019, 110, 117–130. [Google Scholar] [CrossRef]
- Turner, N.; Hershcovis, M.S.; Reich, T.C.; Totterdell, P. Work–family interference, psychological distress, and workplace injuries. J. Occup. Organ. Psychol. 2014, 87, 715–732. [Google Scholar] [CrossRef] [Green Version]
- Chau, N.; Bourgkard, E.; Bhattacherjee, A.; Ravaud, J.-F.; Choquet, M.; Mur, J.-M.; The Lorhandicap Group. Associations of job, living conditions and lifestyle with occupational injury in working population: A population-based study. Int. Arch. Occup. Environ. Health 2008, 81, 379–389. [Google Scholar] [CrossRef]
- Cooper, C.L.; Rout, U.; Faragher, B. Mental health, job satisfaction, and job stress among general practitioners. BMJ 1989, 298, 366–370. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lu, L.; Cooper, C.L.; Chen, Y.C.; Hsu, C.H.; Wu, H.L.; Shih, J.B.; Li, C.H. Chinese version of the OSI: A validation study. Work Stress 1997, 11, 79–86. [Google Scholar] [CrossRef]
- Siu, O.-l.; Lu, L.; Cooper, C.L. Managerial stress in Hong Kong and Taiwan: A comparative study. J. Manag. Psychol. 1999, 14, 6–25. [Google Scholar] [CrossRef]
- Chen, W.Q.; Wong, T.W.; Yu, T.S. Influence of occupational stress on mental health among Chinese off-shore oil workers. Scand. J. Public Health 2009, 37, 766–773. [Google Scholar] [CrossRef]
- Che, X.X.; Zhou, Z.E.; Kessler, S.R.; Spector, P.E. Stressors beget stressors: The effect of passive leadership on employee health through workload and work–family conflict. Work Stress 2017, 31, 338–354. [Google Scholar] [CrossRef]
- Greenhaus, J.H.; Allen, T.D.; Spector, P.E. Health consequences of work–family conflict: The dark side of the work–family interface. Res. Occup. Stress Well Being 2006, 5, 61–98. [Google Scholar] [CrossRef]
- Janzen, B.L.; Muhajarine, N.; Kelly, I.W. Work-family conflict, and psychological distress in men and women among Canadian police officers. Psychol. Rep. 2007, 100, 556–562. [Google Scholar] [CrossRef]
- Van Hoffen, M.F.; Rijnhart, J.J.; Norder, G.; Labuschagne, L.J.; Twisk, J.W. Distress, Work Satisfaction, and Work Ability are Mediators of the Relation Between Psychosocial Working Conditions and Mental Health-Related Long-Term Sickness Absence. J. Occup. Rehabil. 2021, 31, 419–430. [Google Scholar] [CrossRef]
- Kalliath, P.; Kalliath, T. Does job satisfaction mediate the relationship between work–family conflict and psychological strain? A study of Australian social workers. Asia Pac. J. Soc. Work Dev. 2013, 23, 91–105. [Google Scholar] [CrossRef]
- Garbarino, S.; Guglielmi, O.; Sannita, W.G.; Magnavita, N.; Lanteri, P. Sleep and mental health in truck drivers: Descriptive review of the current evidence and proposal of strategies for primary prevention. Int. J. Environ. Res. Public Health 2018, 15, 1852. [Google Scholar] [CrossRef] [Green Version]
- Johnson, J.; Louch, G.; Dunning, A.; Johnson, O.; Grange, A.; Reynolds, C.; Hall, L.; O’Hara, J. Burnout mediates the association between depression and patient safety perceptions: A cross-sectional study in hospital nurses. J. Adv. Nurs. 2017, 73, 1667–1680. [Google Scholar] [CrossRef]
- Mirza, M.Z.; Isha, A.S.N.; Memon, M.A.; Azeem, S.; Zahid, M. Psychosocial safety climate, safety compliance and safety participation: The mediating role of psychological distress. J. Manag. Organ. 2019, 1–16. [Google Scholar] [CrossRef]
- Siu, O.-l.; Phillips, D.R.; Leung, T.-w. Safety climate and safety performance among construction workers in Hong Kong: The role of psychological strains as mediators. Accid. Anal. Prev. 2004, 36, 359–366. [Google Scholar] [CrossRef]
- Zheng, L.; Xiang, H.; Song, X.; Wang, Z. Nonfatal unintentional injuries and related factors among male construction workers in central China. Am. J. Ind. Med. 2010, 53, 588–595. [Google Scholar] [CrossRef] [PubMed]
- Het, S.; Schoofs, D.; Rohleder, N.; Wolf, O.T. Stress-induced cortisol level elevations are associated with reduced negative affect after stress: Indications for a mood-buffering cortisol effect. Psychosom. Med. 2012, 74, 23–32. [Google Scholar] [CrossRef] [Green Version]
- Jansen, N.W.; Kant, I.; Kristensen, T.S.; Nijhuis, F.J. Antecedents and consequences of work–family conflict: A prospective cohort study. J. Occup. Environ. Med. 2003, 45, 479–491. [Google Scholar] [CrossRef]
- Williams, A.; Franche, R.-L.; Ibrahim, S.; Mustard, C.A.; Layton, F.R. Examining the relationship between work-family spillover and sleep quality. J. Occup. Health Psychol. 2006, 11, 27. [Google Scholar] [CrossRef] [PubMed]
- Cheng, S.Y.; Lin, P.C.; Chang, Y.K.; Lin, Y.K.; Lee, P.H.; Chen, S.R. Sleep quality mediates the relationship between work-family conflicts and the self-perceived health status among hospital nurses. J. Nurs. Manag. 2019, 27, 381–387. [Google Scholar] [CrossRef]
- Aazami, S.; Mozafari, M.; Shamsuddin, K.; Akmal, S. Work-family conflict and sleep disturbance: The Malaysian working women study. Ind. Health 2016, 54, 50–57. [Google Scholar] [CrossRef] [Green Version]
- Jacobsen, H.B.; Reme, S.E.; Sembajwe, G.; Hopcia, K.; Stiles, T.C.; Sorensen, G.; Porter, J.H.; Marino, M.; Buxton, O.M. Work stress, sleep deficiency, and predicted 10-year cardiometabolic risk in a female patient care worker population. Am. J. Ind. Med. 2014, 57, 940–949. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lapierre, L.M.; Hammer, L.B.; Truxillo, D.M.; Murphy, L.A. Family interference with work and workplace cognitive failure: The mitigating role of recovery experiences. J. Vocat. Behav. 2012, 81, 227–235. [Google Scholar] [CrossRef]
- Parkes, K.R. Psychosocial aspects of stress, health and safety on North Sea installations. Scand. J. Work Environ. Health 1998, 24, 321–333. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sagherian, K.; Clinton, M.E.; Abu-Saad Huijer, H.; Geiger-Brown, J. Fatigue, work schedules, and perceived performance in bedside care nurses. Workplace Health Saf. 2017, 65, 304–312. [Google Scholar] [CrossRef] [PubMed]
- Chan, M. Fatigue: The most critical accident risk in oil and gas construction. Constr. Manag. Econ. 2011, 29, 341–353. [Google Scholar] [CrossRef]
- Li, F.; Jiang, L.; Yao, X.; Li, Y. Job demands, job resources and safety outcomes: The roles of emotional exhaustion and safety compliance. Accid. Anal. Prev. 2013, 51, 243–251. [Google Scholar] [CrossRef]
- Fang, D.; Jiang, Z.; Zhang, M.; Wang, H. An experimental method to study the effect of fatigue on construction workers’ safety performance. Saf. Sci. 2015, 73, 80–91. [Google Scholar] [CrossRef]
- Whiteoak, J.W.; Mohamed, S. Employee engagement, boredom and frontline construction workers feeling safe in their workplace. Accid. Anal. Prev. 2016, 93, 291–298. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lovibond, P.F.; Lovibond, S.H. The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behav. Res. Ther. 1995, 33, 335–343. [Google Scholar] [CrossRef]
- Crawford, J.R.; Henry, J.; Crombie, C.; Taylor, E. Normative data for the HADS from a large non-clinical sample. Br. J. Clin. Psychol. 2001, 40, 429–434. [Google Scholar] [CrossRef]
- Zigmond, A.S.; Snaith, R.P. The hospital anxiety and depression scale. Acta Psychiatr. Scand. 1983, 67, 361–370. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- McKelvey, R.S.; Webb, J.A. A prospective study of psychological distress related to refugee camp experience. Aust. N. Z. J. Psychiatry 1997, 31, 549–554. [Google Scholar] [CrossRef] [PubMed]
- Parloff, M.; Kelman, H.; Frank, J. Comfort, effectiveness, and self-awareness as criteria of improvement in psychotherapy. Am. J. Psychiatry 1954, 111, 343. [Google Scholar] [CrossRef]
- Radloff, L.S. The CES-D scale: A self-report depression scale for research in the general population. Appl. Psychol. Meas. 1977, 1, 385–401. [Google Scholar] [CrossRef]
- Michielsen, H.J.; De Vries, J.; Van Heck, G.L. Psychometric qualities of a brief self-rated fatigue measure: The Fatigue Assessment Scale. J. Psychosom. Res. 2003, 54, 345–352. [Google Scholar] [CrossRef]
- Michielsen, H.J.; De Vries, J.; Van Heck, G.L.; Van de Vijver, F.J.; Sijtsma, K. Examination of the dimensionality of fatigue. Eur. J. Psychol. Assess. 2004, 20, 39–48. [Google Scholar] [CrossRef]
- Chalder, T.; Berelowitz, G.; Pawlikowska, T.; Watts, L.; Wessely, S.; Wright, D.; Wallace, E. Development of a fatigue scale. J. Psychosom. Res. 1993, 37, 147–153. [Google Scholar] [CrossRef] [Green Version]
- Jackson, C. The Chalder fatigue scale (CFQ 11). Occup. Med. 2015, 65, 86. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Loge, J.H.; Ekeberg, Ø.; Kaasa, S. Fatigue in the general Norwegian population: Normative data and associations. J. Psychosom. Res. 1998, 45, 53–65. [Google Scholar] [CrossRef]
- Smets, E.; Garssen, B.; Bonke, B.; De Haes, J. The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. J. Psychosom. Res. 1995, 39, 315–325. [Google Scholar] [CrossRef] [Green Version]
- Lu, C.-S.; Yang, C.-S. Safety leadership and safety behavior in container terminal operations. Saf. Sci. 2010, 48, 123–134. [Google Scholar] [CrossRef]
- Neal, A.; Griffin, M.A. A study of the lagged relationships among safety climate, safety motivation, safety behavior, and accidents at the individual and group levels. J. Appl. Psychol. 2006, 91, 946. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zacharatos, A. An Organization and Employee-Level Investigation of the Relationship between High-Performance Work Systems and Workplace Safety; Queen’s University: Kingston, ON, Canada, 2001. [Google Scholar]
- Vinodkumar, M.; Bhasi, M. Safety management practices and safety behaviour: Assessing the mediating role of safety knowledge and motivation. Accid. Anal. Prev. 2010, 42, 2082–2093. [Google Scholar] [CrossRef]
- MacKinnon, D.P.; Warsi, G.; Dwyer, J.H. A simulation study of mediated effect measures. Multivar. Behav. Res. 1995, 30, 41–62. [Google Scholar] [CrossRef] [Green Version]
- MacKinnon, D.P.; Fairchild, A.J.; Fritz, M.S. Mediation analysis. Annu. Rev. Psychol. 2007, 58, 593–614. [Google Scholar] [CrossRef]
- Preacher, K.J.; Hayes, A.F. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 2008, 40, 879–891. [Google Scholar] [CrossRef]
- Choudhry, R.M.; Fang, D. Why operatives engage in unsafe work behavior: Investigating factors on construction sites. Saf. Sci. 2008, 46, 566–584. [Google Scholar] [CrossRef]
- Fang, D.; Wu, C.; Wu, H. Impact of the supervisor on worker safety behavior in construction projects. J. Manag. Eng. 2015, 31, 04015001. [Google Scholar] [CrossRef]
- Guo, B.H.; Yiu, T.W. Developing leading indicators to monitor the safety conditions of construction projects. J. Manag. Eng. 2015, 32, 04015016. [Google Scholar] [CrossRef]
- Mearns, K.; Flin, R.; Gordon, R.; Fleming, M. Human and organizational factors in offshore safety. Work Stress 2001, 15, 144–160. [Google Scholar] [CrossRef]
- Smith, T.D.; Hughes, K.; DeJoy, D.M.; Dyal, M.-A. Assessment of relationships between work stress, work-family conflict, burnout and firefighter safety behavior outcomes. Saf. Sci. 2018, 103, 287–292. [Google Scholar] [CrossRef]
- Tucker, J.S.; Sinclair, R.R.; Mohr, C.D.; Adler, A.B.; Thomas, J.L.; Salvi, A.D. Stress and counterproductive work behavior: Multiple relationships between demands, control, and soldier indiscipline over time. J. Occup. Health Psychol. 2009, 14, 257. [Google Scholar] [CrossRef] [PubMed]
- Andersen, M.B.; Williams, J.M. A model of stress and athletic injury: Prediction and prevention. J. Sport Exerc. Psychol. 1988, 10, 294–306. [Google Scholar] [CrossRef] [Green Version]
- Williams, J.M.; Andersen, M.B. Psychosocial Antecedents of Sport Injury and Interventions for Risk Reduction. In Handbook of Sport Psychology; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2007; pp. 379–403. [Google Scholar]
- Hemingway, M.A.; Smith, C.S. Organizational climate and occupational stressors as predictors of withdrawal behaviours and injuries in nurses. J. Occup. Organ. Psychol. 1999, 72, 285–299. [Google Scholar] [CrossRef]
- Probst, T.M. Layoffs and tradeoffs: Production, quality, and safety demands under the threat of job loss. J. Occup. Health Psychol. 2002, 7, 211. [Google Scholar] [CrossRef]
- Cullen, J.C.; Hammer, L.B. Developing and testing a theoretical model linking work-family conflict to employee safety. J. Occup. Health Psychol. 2007, 12, 266. [Google Scholar] [CrossRef]
- Wei, W.; Guo, M.; Ye, L.; Liao, G.; Yang, Z. Work-family conflict and safety participation of high-speed railway drivers: Job satisfaction as a mediator. Accid. Anal. Prev. 2016, 95, 97–103. [Google Scholar] [CrossRef]
- Smith, T.D.; DeJoy, D.M. Occupational injury in America: An analysis of risk factors using data from the General Social Survey (GSS). J. Saf. Res. 2012, 43, 67–74. [Google Scholar] [CrossRef]
- Cummins, R.C. Job stress and the buffering effect of supervisory support. Group Organ. Stud. 1990, 15, 92–104. [Google Scholar] [CrossRef]
- Leung, M.-y.; Chan, I.Y.S.; Yu, J. Preventing construction worker injury incidents through the management of personal stress and organizational stressors. Accid. Anal. Prev. 2012, 48, 156–166. [Google Scholar] [CrossRef]
- Biggs, H.; Wang, X.; Mohamed, S.; Colquhoun, S.; Dovan, N. Challenges for the FIFO/DIDO Workforce in the Australian Construction Industry: Impacts on Health, Safety and Relationships. In Proceedings of the CIB World Building Congress 2016: Volume II-Environmental Opportunies and Challenges; Tampere University of Technology: Tampere, Finland, 2016; pp. 283–292. [Google Scholar]
- Xiao, W.; Zhou, L.; Wu, Q.; Zhang, Y.; Miao, D.; Zhang, J.; Peng, J. Effects of person-vocation fit and core self-evaluation on career commitment of medical university students: The mediator roles of anxiety and career satisfaction. Int. J. Ment. Health Syst. 2014, 8, 1–6. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sharma, J.; Dhar, R.L.; Tyagi, A. Stress as a mediator between work–family conflict and psychological health among the nursing staff: Moderating role of emotional intelligence. Appl. Nurs. Res. 2016, 30, 268–275. [Google Scholar] [CrossRef]
- Lepore, S.J.; Evans, G.W.; Schneider, M.L. Dynamic role of social support in the link between chronic stress and psychological distress. J. Personal. Soc. Psychol. 1991, 61, 899. [Google Scholar] [CrossRef]
- Kartam, N.; Flood, I.; Koushki, P. Construction safety in Kuwait: Issues, procedures, problems, and recommendations. Saf. Sci. 2000, 36, 163–184. [Google Scholar] [CrossRef]
- Day, A.J.; Brasher, K.; Bridger, R.S. Accident proneness revisited: The role of psychological stress and cognitive failure. Accid. Anal. Prev. 2012, 49, 532–535. [Google Scholar] [CrossRef] [PubMed]
- Schieman, S.; Young, M.C. Are communications about work outside regular working hours associated with work-to-family conflict, psychological distress and sleep problems? Work Stress 2013, 27, 244–261. [Google Scholar] [CrossRef]
- Van Hooff, M.L.; Geurts, S.A.; Kompier, M.A.; Taris, T.W. Work–home interference: How does it manifest itself from day to day? Work Stress 2006, 20, 145–162. [Google Scholar] [CrossRef]
- Chan, M. Accident Risk Management in Oil and Gas Construction Projects in Mainland China; University of Sydney: Sydney, Australia, 2009. [Google Scholar]
- Lauridsen, Ø.; Tronsmoen, S.; Berland, J.; Gitlesen, J.; Ringstad, A.; Pedersen, T.; Eriksson, L.; Nome, T. Shift-Work and Health; Phillips Petroleum Company/Rogaland Research: Stavanger, Norway, 1991. [Google Scholar]
- Henry, P.; Hamilton, K.; Watson, S.; MacDonald, N. FIFO/DIDO Mental Health Research Report; Lifeline WA: Perth, WA, Australia, 2013. [Google Scholar]
- Strahan, C.; Watson, B.; Lennonb, A. Can organisational safety climate and occupational stress predict work-related driver fatigue? Transp. Res. Part F Traffic Psychol. Behav. 2008, 11, 418–426. [Google Scholar] [CrossRef] [Green Version]
- Harrison, J.E.; Mandryk, J.A.; Frommer, M.S. Work-related road fatalities in Australia, 1982–1984. Accid. Anal. Prev. 1993, 25, 443–451. [Google Scholar] [CrossRef]
- Raslear, T.G.; Gertler, J.; DiFiore, A. Work schedules, sleep, fatigue, and accidents in the US railroad industry. Fatigue Biomed Health Behav. 2013, 1, 99–115. [Google Scholar] [CrossRef]
- Powell, R.I.; Copping, A.G. Measuring fatigue-related impairment in the workplace. J. Eng. Des. Technol. 2016, 14, 507–525. [Google Scholar] [CrossRef]
- Saxena, A.; Garg, N.; Punia, B.; Prasad, A. Exploring role of Indian workplace spirituality in stress management: A study of oil and gas industry. J. Organ. Chang. Manag. 2020, 33, 779–803. [Google Scholar] [CrossRef]
- King, D.B. Rethinking Claims of Spiritual Intelligence: A Definition, Model, and Measure. Unpublished. Master’s Thesis, Trent University, Peterborough, ON, Canada, 2008. [Google Scholar]
- Lazarus, R.S. Psychological stress in the workplace. In Occupational Stress: A Handbook; CRC Press: Boca Raton, FL, USA, 1995; Volume 1, pp. 3–14. [Google Scholar]
- García-León, M.Á.; Pérez-Mármol, J.M.; Gonzalez-Pérez, R.; del Carmen García-Ríos, M.; Peralta-Ramírez, M.I. Relationship between resilience and stress: Perceived stress, stressful life events, HPA axis response during a stressful task and hair cortisol. Physiol. Behav. 2019, 202, 87–93. [Google Scholar] [CrossRef] [PubMed]
- Oken, B.S. A Systems Approach to Stress and Resilience in Humans: Mindfulness Meditation, Aging, and Cognitive Function. Doctoral Dissertation, Portland State University, Portland, OR, USA, 2016. [Google Scholar]
Construct | Variable | Scale | Supporting Literature |
---|---|---|---|
Occupational Stressors | Responsibilities towards family | - | [11,12] |
Living environment | - | ||
Mental Health | Anxiety | DASS21 | [52] |
HADS | [53,54] | ||
HSCL-25 | [55,56] | ||
Depression | DASS21 | [52] | |
HSCL-25 | [55,56] | ||
CES-D | [57] | ||
Fatigue | Physical fatigue | FAS | [58,59] |
FQ | [60,61,62] | ||
Mental fatigue | FAS | [58,59] | |
FQ | [60,61,62] | ||
MFI | [63] | ||
Safety Behaviour | Safety compliance | - | [64] |
- | [65] | ||
- | [66] | ||
Safety participation | - | [67] | |
- | [65] | ||
- | [66] |
Demographic Characteristics | Frequency | Percent% |
---|---|---|
Nationality | ||
Indian | 295 | 76.2 |
Egyptian | 35 | 9.0 |
Filipino | 20 | 5.2 |
Thai | 15 | 3.9 |
Others | 22 | 5.7 |
Age (years) | ||
≤20 | 1 | 0.3 |
20–29 | 75 | 19.4 |
30–39 | 164 | 42.4 |
40–49 | 106 | 27.4 |
50–59 | 36 | 9.3 |
≥60 | 5 | 1.3 |
Marital Status | ||
Single | 76 | 19.6 |
Married/Living with a partner | 311 | 80.4 |
Last Trip Back Home | ||
1 month ago | 152 | 39.0 |
3 months ago | 57 | 14.7 |
6 months ago | 68 | 17.6 |
1 year ago | 83 | 21.4 |
2 years ago | 24 | 6.2 |
Others | 4 | 1.0 |
Days off/Weekends | ||
At Camp | 301 | 77.8 |
Off Camp | 86 | 22.2 |
Regression Path | B | P | LLCI | ULCI |
---|---|---|---|---|
Path A (RTF to ANX) | 0.211 | <0.001 | 0.110 | 0.311 |
Path B (ANX to SFP) | −0.204 | <0.001 | −0.279 | −0.129 |
Path C (total effect of RTF on SFP) | −0.105 | <0.01 | −0.183 | −0.027 |
Path C’ (direct effect of RTF on SFP) | −0.062 | =0.113 | −0.139 | 0.015 |
Path A ∗ B (indirect effect of the RTF on the SFP through the ANX) | −0.043 | −0.070 | −0.019 | |
Total effects R2 = 1.2%, F(2, 384) = 17.98, p < 0.001 |
Regression Path (LE, ANX, SFC) | B | P | LLCI | ULCI |
---|---|---|---|---|
Path A (LE to ANX) | 0.416 | <0.001 | 0.316 | 0.515 |
Path B (ANX to SFC) | −0.210 | <0.001 | −0.293 | −0.128 |
Path C (total effect of LE on SFC) | −0.044 | =0.302 | −0.129 | 0.040 |
Path C’ (direct effect of LE on SFC) | 0.043 | =0.344 | −0.046 | 0.132 |
Path A ∗ B (indirect effect of the LE on the SFC through the ANX) | −0.087 | −0.133 | −0.051 | |
Total effects R2 = 0.1%, F(2, 384) = 13.09, p < 0.001 | ||||
Regression Path (LE, ANX, SFP) | B | P | LLCI | ULCI |
Path A (LE to ANX) | 0.416 | <0.001 | 0.316 | 0.515 |
Path B (ANX to SFP) | −0.211 | <0.001 | −0.291 | −0.131 |
Path C (total effect of LE on SFP) | −0.104 | <0.05 | −0.186 | −0.021 |
Path C’ (direct effect of LE on SFP) | −0.016 | =0.713 | −0.102 | 0.070 |
Path A ∗ B (indirect effect of the LE on the SFP through the ANX) | −0.088 | −0.131 | −0.052 | |
Total effects R2 = 1.5%, F(2, 384) = 16.69, p < 0.001 |
Regression Path (RTF, DPR, SFC) | B | P | LLCI | ULCI |
---|---|---|---|---|
Path A (RTF to DPR) | 0.260 | <0.001 | 0.170 | 0.350 |
Path B (DPR to SFC) | −0.158 | =0.001 | −0.289 | −0.134 |
Path C (total effect of RTF on SFC) | 0.039 | =0.345 | −0.042 | 0.119 |
Path C’ (direct effect of RTF on SFC) | 0.080 | =0.059 | −0.003 | 0.162 |
Path A ∗ B (indirect effect of the RTF on the SFC through the DPR) | −0.0410 | −0.072 | −0.018 | |
Total effects R2 = −0.6%, F(2, 384) = 6.62, p < 0.001 | ||||
Regression Path (RTF, DPR, SFP) | B | P | LLCI | ULCI |
Path A (RTF to DPR) | 0.260 | <0.001 | 0.170 | 0.350 |
Path B (DPR to SFP) | −0.096 | <0.05 | −0.182 | −0.009 |
Path C (total effect of RTF on SFP) | −0.105 | <0.01 | −0.182 | −0.027 |
Path C’ (direct effect of RTF on SFP) | −0.080 | =0.051 | −0.161 | 0.001 |
Path A* B (indirect effect of the RTF on the SFP through the DPR) | −0.025 | −0.483 | −0.004 | |
Total effects R2 = 0.8%, F(2, 384) = 5.95, p < 0.01 |
Regression Path (LE, DPR, SFC) | B | P | LLCI | ULCI |
---|---|---|---|---|
Path A (LE to DPR) | 0.348 | <0.001 | 0.255 | 0.440 |
Path B (DPR to SFC) | −0.135 | <0.001 | −0.226 | −0.044 |
Path C (total effect of LE on SFC) | −0.044 | =0.302 | −0.129 | 0.040 |
Path C’ (direct effect of LE on SFC) | 0.002 | =0.958 | −0.087 | 0.092 |
Path A ∗ B (indirect effect of the LE on the SFC through the DPR) | −0.047 | −0.081 | −0.019 | |
Total effects R2 = 0.3%, F(2, 384) = 4.78, p < 0.01 | ||||
Regression Path (LE, DPR, SFP) | B | P | LLCI | ULCI |
Path A (LE to DPR) | 0.384 | <0.001 | 0.255 | 0.440 |
Path B (DPR to SFP) | −0.094 | <0.05 | −0.183 | −0.005 |
Path C (total effect of LE on SFP) | −0.104 | <0.05 | −0.186 | −0.021 |
Path C’ (direct effect of LE on SFP) | −0.071 | =0.111 | −0.159 | 0.017 |
Path A ∗ B (indirect effect of the LE on the SFP through the DPR) | −0.033 | −0.062 | −0.005 | |
Total effects R2 = 0.9%, F(2, 384) = 5.26, p < 0.01 |
Regression Path (RTF, PFT, SFC) | B | P | LLCI | ULCI |
---|---|---|---|---|
Path A (RTF to PFT) | 0.304 | <0.001 | 0.201 | 0.407 |
Path B (PFT to SFC) | −0.144 | <0.001 | −0.221 | −0.067 |
Path C (total effect of RTF on SFC) | 0.039 | =0.345 | −0.042 | 0.119 |
Path C’ (direct effect of RTF on SFC) | 0.082 | =0.05 | 0.000 | 0.165 |
Path A ∗ B (indirect effect of the RTF on the SFC through the PFT) | −0.044 | −0.077 | −0.018 | |
Total effects R2 = −0.7%, F(2, 384) = 7.17, p = 0.001 | ||||
Regression Path (RTF, PFT, SFP) | B | P | LLCI | ULCI |
Path A (RTF to PFT) | 0.304 | <0.001 | 0.201 | 0.407 |
Path B (PFT to SFP) | −0.111 | <0.01 | −0.186 | −0.035 |
Path C (total effect of RTF on SFP) | −0.105 | <0.01 | −0.183 | −0.027 |
Path C’ (direct effect of RTF on SFP) | −0.072 | =0.082 | −0.152 | 0.009 |
Path A ∗ B (indirect effect of the RTF on the SFP through the PFT) | −0.043 | − | −0.019 | |
Total effects R2 = 1.0%, F(2, 384) = 7.76, p < 0.001 |
Regression Path (LE, PFT, SFC) | B | P | LLCI | ULCI |
---|---|---|---|---|
Path A (LE to PFT) | 0.421 | <0.001 | 0.307 | 0.517 |
Path B (PFT to SFC) | −0.124 | <0.01 | −0.204 | −0.044 |
Path C (total effect of LE on SFC) | −0.044 | =0.302 | −0.129 | 0.040 |
Path C’ (direct effect of LE on SFC) | 0.007 | =0.884 | −0.083 | 0.097 |
Path A ∗ B (indirect effect of the LE on the SFC through the PFT) | −0.087 | −0.133 | −0.051 | |
Total effects R2 = 0.3%, F(2, 384) = 5.20, p < 0.01 | ||||
Regression Path (LE, PFT, SFP) | B | P | LLCI | ULCI |
Path A (LE to PFT) | 0.412 | <0.001 | 0.317 | 0.517 |
Path B (PFT to SFP) | −0.111 | <0.001 | −0.189 | −0.033 |
Path C (total effect of LE on SFP) | −0.104 | <0.05 | −0.186 | −0.021 |
Path C’ (direct effect of LE on SFP) | −0.058 | =0.194 | −0.146 | 0.030 |
Path A ∗ B (indirect effect of the LE on the SFP through the PFT) | −0.046 | −0.079 | −0.015 | |
Total effects R2 = 1.1%, F(2, 384) = 7.07, p = 0.001 |
Regression Path (RTF, MFT, SFC) | B | P | LLCI | ULCI |
---|---|---|---|---|
Path A (RTF to MFT) | 0.309 | <0.001 | 0.201 | 0.407 |
Path B (MFT to SFC) | −0.239 | <0.001 | −0.321 | −0.158 |
Path C (total effect of RTF on SFC) | 0.039 | =0.345 | −0.042 | 0.119 |
Path C’ (direct effect of RTF on SFC) | 0.113 | <0.01 | 0.031 | 0.194 |
Path A ∗ B (indirect effect of the RTF on the SFC through the MFT) | −0.074 | −0.112 | −0.044 | |
Total effects R2 = −1.5%, F(2, 384) = 17.15, p < 0.001 | ||||
Regression Path (RTF, MFT, SFP) | B | P | LLCI | ULCI |
Path A (RTF to MFT) | 0.309 | <0.001 | 0.204 | 0.404 |
Path B (MFT to SFP) | −0.211 | <0.01 | −0.291 | −0.131 |
Path C (total effect of RTF on SFP) | −0.105 | <0.01 | −0.183 | −0.027 |
Path C’ (direct effect of RTF on SFP) | −0.040 | =0.322 | −0.120 | 0.039 |
Path A ∗ B (indirect effect of the RTF on the SFP through the MFT) | −0.065 | −0.097 | −0.039 | |
Total effects R2 = 1.6%, F(2, 384) = 13.31, p < 0.001 |
Regression Path (LE, MFT, SFC) | B | P | LLCI | ULCI |
---|---|---|---|---|
Path A (RTF to ANX) | 0.211 | <0.001 | 0.110 | 0.311 |
Path B (ANX to SFC) | −0.212 | <0.001 | −0.289 | −0.134 |
Path C (total effect of RTF on SFC) | 0.039 | =0.345 | −0.042 | 0.119 |
Path C’ (direct effect of RTF on SFC) | 0.083 | <0.05 | 0.004 | 0.163 |
Path A ∗ B (indirect effect of the RTF on the SFC through the ANX) | −0.0446 | −0.077 | −0.020 | |
Total effects R2 = −0.8%, F(2, 384) = 14.88, p < 0.001 | ||||
Regression Path (LE, MFT, SFP) | B | P | LLCI | ULCI |
Path A (LE to MFT) | 0.461 | <0.001 | 0.366 | 0.555 |
Path B (MFT to SFP) | −0.223 | <0.001 | −0.308 | −0.139 |
Path C (total effect of LE on SFP) | −0.104 | <0.05 | −0.186 | −0.021 |
Path C’ (direct effect of LE on SFP) | −0.001 | =0.984 | −0.090 | 0.088 |
Path A ∗ B (indirect effect of the LE on the SFP through the MFT) | −0.103 | −0.143 | −0.066 | |
Total effects R2 = 1.6%, F(2, 384) = 16.78, p < 0.001 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Alroomi, A.S.; Mohamed, S. Occupational Stressors and Safety Behaviour among Oil and Gas Workers in Kuwait: The Mediating Role of Mental Health and Fatigue. Int. J. Environ. Res. Public Health 2021, 18, 11700. https://doi.org/10.3390/ijerph182111700
Alroomi AS, Mohamed S. Occupational Stressors and Safety Behaviour among Oil and Gas Workers in Kuwait: The Mediating Role of Mental Health and Fatigue. International Journal of Environmental Research and Public Health. 2021; 18(21):11700. https://doi.org/10.3390/ijerph182111700
Chicago/Turabian StyleAlroomi, Anwar S., and Sherif Mohamed. 2021. "Occupational Stressors and Safety Behaviour among Oil and Gas Workers in Kuwait: The Mediating Role of Mental Health and Fatigue" International Journal of Environmental Research and Public Health 18, no. 21: 11700. https://doi.org/10.3390/ijerph182111700
APA StyleAlroomi, A. S., & Mohamed, S. (2021). Occupational Stressors and Safety Behaviour among Oil and Gas Workers in Kuwait: The Mediating Role of Mental Health and Fatigue. International Journal of Environmental Research and Public Health, 18(21), 11700. https://doi.org/10.3390/ijerph182111700