DOI QR코드

DOI QR Code

Influence of Cushioning Variables in the Workplace and in the Family on the Probability of Suffering Stress

  • 투고 : 2015.11.03
  • 심사 : 2016.02.02
  • 발행 : 2016.09.30

초록

Stress at work and in the family is a very common issue in our society that generates many health-related problems. During recent years, numerous studies have sought to define the term stress, raising many contradictions that various authors have studied. Other authors have attempted to establish some criteria, in subjective and not very quantitative ways, in an attempt to reduce and even to eliminate stressors and their effects at work and in the family context. The purpose of this study was to quantify so-called cushioning variables, such as control, social support, home/work life conciliation, and even sports and leisure activities, with the purpose of, as much as possible, reducing the negative effects of stress, which seriously affects the health of workers. The study employs data from the Fifth European Working Conditions Survey, in which nearly 44,000 interviewees from 34 countries in the European Union participated. We constructed a probabilistic model based on a Bayesian network, using variables from both the workplace and the family, the aforementioned cushioning variables, as well as the variable stress. If action is taken on the above variables, then the probabilities of suffering high levels of stress may be reduced. Such action may improve the quality of life of people at work and in the family.

키워드

참고문헌

  1. Cox T, Mackay CJ. A transactional approach to occupational stress. In: Corlett EN, Richardson J, editors. Stress, work design and productivity. New York (NY): Wiley; 1981. p. 10-34.
  2. Selye H, Ogilvie HS. The stress of life. New York (NY): McGraw-Hill; 1956.
  3. Edwards JR. The determinants and consequences of coping with stress. In: Cooper CL, Payne R, editors. Causes, coping and consequences of stress at work. New York (NY): John Wiley & Sons; 1988.
  4. Rundmo T. Perceived risk, safety status, and job stress among injured and noninjured employees on offshore petroleum installations. J Saf Res 1995;26: 87-97. https://doi.org/10.1016/0022-4375(95)00008-E
  5. McGrath JE, Altman I. Social and psychological factors in stress. New York (NY): University at Illinois Holt, Rinehart and Winston; 1970.
  6. Kopelman RE. Job redesign and productivity: a review of the evidence. New York (NY): John Wiley & Sons; 1985.
  7. Semmer NK. Job stress interventions and the organization of work. Scand J Work Environ Health 2006;32:515-27. https://doi.org/10.5271/sjweh.1056
  8. Peiro JM. Job stress: an individual and collective perspective. Valencia (Spain): INSHT (Instituto Nacional de Seguridad e Higiene en el Trabajo); 2001. Publication 2001-13. p. 13-38.
  9. Gil-Monte PR, Peiro JM. The burnout syndrome at work. An occupational disease in the welfare society. Madrid (Spain): Pyramid Psychology; 1997.
  10. Hall DT, Hall FS. Stress and the two-career couple. In: Cooper CL, Payne RL, editors. Current concerns in occupational stress. London (UK): John Wiley and Sons; 1980. p. 243-6.
  11. Karasek R. Job demands, job decision latitude, and mental strain: implications for job redesign. New York (NY): Administrative Science Quarterly; 1979.
  12. Peiro JM. The model "Friend": contextualizing frame development and RR.HH management in organizations. Psychol Pap 1999;72:3-15.
  13. Peiro JM, Salvador A. Control of work stress. Madrid (Spain): Eudema Psicolology; 1993.
  14. Johnson JV, Hall EM, 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;15:271-9. https://doi.org/10.5271/sjweh.1852
  15. Artazcoz L, Borrell C, Benach J, Cortes I, Rohlfs I. Women, family demands and health: The importance of employment status and socio-economic position. Soc Sci Med 2004;59:263-74. https://doi.org/10.1016/j.socscimed.2003.10.029
  16. Grote NK, Clark MS, Moore A. Perceptions of injustice in family work: the role of psychological distress. J Fam Psychol 2004;18:480-92. https://doi.org/10.1037/0893-3200.18.3.480
  17. Rodriguez-Suarez J, Agullo-Tomas E. Psicología social y ocio: una articulacion necesaria. (Social psychology and leisure: a necessary articulation.) Psicothema 2002;14:124-33. [in Spanish].
  18. Stanton-Rich HM. The interrelationships of leisure attitude, leisure satisfaction, leisure behavior, intrinsic motivation and burnout among clergy. Human Soc Sci 1996;57:1323.
  19. Stanton-Rich HM, Iso-Ahola SE. Burnout and leisure. J Appl Soc Psychol 1998;28:1931-50. https://doi.org/10.1111/j.1559-1816.1998.tb01354.x
  20. Sanmiquel L, Rossell JM, Vintro C. Study of Spanish mining accidents using data mining techniques. Saf Sci 2015;75:49-55. https://doi.org/10.1016/j.ssci.2015.01.016
  21. Zhou Q, Fang D, Wang X. A method to identify strategies for the improvement of human safety behavior by considering safety climate and personal experience. Saf Sci 2008;46:1406-19. https://doi.org/10.1016/j.ssci.2007.10.005
  22. McCabe B, Loughlin C, Munteanu R, Tucker S, Lam A. Individual safety and health outcomes in the construction industry. Can J Civil Eng 2008;3512: 1455-67.
  23. Ren J, Jenkinson I, Wang J, Xu DL, Yang JB. A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors. J Saf Res 2008;39:87-100. https://doi.org/10.1016/j.jsr.2007.09.009
  24. Galan SF, Mosleh A, Izquierdo JM. Incorporating organizational factors into probabilistic safety assessment of nuclear power plants through canonical probabilistic models. Reliability Eng Syst Saf 2007;92:1131-8. https://doi.org/10.1016/j.ress.2006.07.006
  25. Mohaghegh Z, Mosleh A. Measurement techniques for organizational safety causal models: characterization and suggestions for enhancements. Saf Sci 2009;4710:1398-409.
  26. Martin JE, Rivas T, Matias JM, Taboada J, Arguelles A. A Bayesian network analysis of workplace accidents caused by falls from a height. Saf Sci 2009;47: 206-14. https://doi.org/10.1016/j.ssci.2008.03.004
  27. Garcia-Herrero S, Mariscal MA, Garcia-Rodriguez J, Ritzel DO. Working conditions, psychological/physical symptoms and occupational accidents. Bayesian network models. Saf Sci 2012;50:1760-74. https://doi.org/10.1016/j.ssci.2012.04.005
  28. Castillo E, Gutierrez JM, Hadi AS. Expert systems and probabilistic network models. New York (NY): Springer Verlag; 1997.
  29. Fawcett T. An introduction to ROC analysis. Pattern Recognit Lett 2006;27: 861-74. https://doi.org/10.1016/j.patrec.2005.10.010
  30. Zou KH, O'Malley AJ, Mauri L. Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models. Circulation 2007;115: 654-7. https://doi.org/10.1161/CIRCULATIONAHA.105.594929
  31. Swets J. Signal detection theory and ROC analysis in psychology and diagnostics: collected papers. Mahwah (NY): Lawrence Erlbaum Associates; 1996.
  32. Fogarty J, Baker R, Hudson S. Case studies in the use of ROC curve analysis for sensor-based estimates in human computer interaction. Proceedings of Graphics Interface 2005. Waterloo (Canada): University of Waterloo; 2005.
  33. Fawcett T. ROC graphs: notes and practical considerations for researchers. Palo Alto (CA): Kluwer Academic Publishers; 2004.