Who reported having a high-strain job, low-strain job, active job and passive job? The WIRUS Screening study

English version

Autoři: Tore Bonsaksen ^aff001; Mikkel Magnus Thørrisen ^aff001; Jens Christoffer Skogen ^aff003; Randi Wågø Aas ^aff001
Působiště autorů: Department of Occupational Therapy, Prosthetics and Orthotics, Faculty of Health Sciences, OsloMet–Oslo Metropolitan University, Oslo, Norway ^aff001; Faculty of Health Studies, VID Specialized University, Sandnes, Norway ^aff002; Faculty of Health Sciences, University of Stavanger, Stavanger, Norway ^aff003; Department of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway ^aff004; Alcohol & Drug Research, Stavanger University Hospital, Stavanger, Norway ^aff005; Presenter–Making Sense of Science, Stavanger, Norway ^aff006
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0227336

Souhrn

Objective

The Job Demands and Control model classifies job types as active, passive, low-strain or high-strain, based on a combination of job demands and control. While studies have shown high-strain jobs to have adverse consequences for health and work participation, prognostic factors for the four job types have been less explored. The aim of this study was to assess the associations between sociodemographic factors and job descriptors and being in high-strain, low-strain, active and passive jobs.

Methods

The WIRUS Screening study targeted Norwegian employees in private and public enterprises. In this study, associations with job types among 4,487 employees were investigated with binary logistic regression analyses, adjusting for sociodemographic and job-related variables.

Results

In fully adjusted models, high-strain job was associated with female gender; lower education; shift work; and doing work outside the workplace. Low-strain job was associated with opposite scores on the same variables, and with lower job position. Active job was associated with lower age; female gender; higher levels of education; higher job position level; shift work; and not doing work outside the workplace. Passive job was associated with opposite scores on the same variables.

Conclusions

The study corroborates the role gender and education have for experiencing the job, and expands on existing knowledge on the role of job position and irregular working hours and spaces. By identifying factors associated with job types, the prevention of health problems and work disability may become be more targeted.

Klíčová slova:

Employment – Jobs – Schools – Age groups – Educational attainment – Regression analysis – Latitude – Norway

Zdroje

1. Statistics Norway. Work Force Survey, with seasonal adjustments [Arbeidskraftundersøkinga, sesongjusterte tal]. Oslo: Statistics Norway; 2019 [Available from: https://www.ssb.no/akumnd].

2. Statistics Norway. Facts about gender equality [Fakta om likestilling]. Statistics Norway; 2019 [Available from: https://www.ssb.no/befolkning/faktaside/likestilling].

3. Bonsaksen T, Grimholt TK, Skogstad L, Lerdal A, Ekeberg Ø, Heir T, et al. Self-diagnosed depression in the Norwegian general population—associations with neuroticism, extraversion, optimism, and general self-efficacy. BMC Public Health. 2018;18:1076. doi: 10.1186/s12889-018-5990-8 30157827

4. Fryers T, Melzer D, Jenkins R. Social inequalities and the common mental disorders. Soc Psych Psychiatr Epidemiol. 2003;38(5):229–37.

5. Roman PM, Blum TC. The workplace and alcohol problem prevention. Alc Res Health. 2002;26(1):49–57.

6. Harvey SB, Joyce S, Tan L, Johnson A, Nguyen H, Modini M, et al. Developing a mentally healthy workplace: A review of the literature. Sydney: National Mental Health Commission, 2014.

7. Karasek R. Job demands, job decision latitude and mental strain: implications for job redesign. Adm Sci Quart. 1979;24(2):285–308.

8. Karasek RA, Theorell T. Healthy work: stress, productivity and the reconstruction of working life. New York, NY: Basic Books; 1990.

9. de Jonge J, Bosma H, Peter R, Siegrist J. Job strain, effort-reward imbalance and employee well-being: a large-scale cross-sectional study. Soc Sci Med. 2000;50(9):1317–27. doi: 10.1016/s0277-9536(99)00388-3 10728851

10. Williams-Whitt K, White MI, Wagner SL, Schultz IZ, Koehn C, Dionne CE, et al. Job demand and control interventions: a stakeholder-centered best-evidence synthesis of systematic reviews on workplace disability. Int J Occup Environ Med. 2015;6(2):61–78. doi: 10.15171/ijoem.2015.553 25890601

11. Karasek R, Brisson C, Kawakami N, Houtman I, Bongers P, Amick B. The Job Content Questionnaire (JCQ): an instrument for internationally comparative assessments of psychosocial job characteristics. J Occup Health Psychol. 1998;3(4):322–55. doi: 10.1037//1076-8998.3.4.322 9805280

12. Stansfeld S, Candy B. Psychosocial work environment and mental health—a meta-analytic review. Scand J Work Environ Health. 2006;32(6):443–62. doi: 10.5271/sjweh.1050 17173201

13. Netterstrøm B, Conrad N, Bech P, Fink P, Olsen O, Rugulies R, et al. The relation between work-related psychosocial factors and the development of depression. Epidemiol Rev. 2008;30(1):118–32.

14. Duijts SF, Kant I, Swaen GM, Brandt PA, Zeegers MP. A meta-analysis of observational studies identifies predictors of sickness absence. J Clin Epidemiol. 2007;60(11):1105–15. doi: 10.1016/j.jclinepi.2007.04.008 17938051

15. Zeike S, Ansmann L, Lindert L, Samel C, Kowalski C, Pfaff H. Identifying cut-off scores for job demands and job control in nursing professionals: a cross-sectional survey in Germany. BMJ Open. 2018;8(12):e021366. doi: 10.1136/bmjopen-2017-021366 30530574

16. Häusser JA, Mojzisch A, Niesel M, Schulz-Hardt S. Ten years on: A review of recent research on the Job Demand–Control (-Support) model and psychological well-being. Work Stress. 2010;24(1):1–35.

17. Habibi E, Poorabdian S, Shakerian M. Job strain (demands and control model) as a predictor of cardiovascular risk factors among petrochemical personnel. J Educ Health Prom. 2015;4:16.

18. Mortensen J, Dich N, Lange T, Alexanderson K, Goldberg M, Head J, et al. Job strain and informal caregiving as predictors of long-term sickness absence: A longitudinal multi-cohort study. Scand J Work Environ Health. 2017;43(1):5–14. doi: 10.5271/sjweh.3587 27556905

19. Kondo K, Kobayashi Y, Hirokawa K, Tsutsumi A, Kobayashi F, Haratani T, et al. Job strain and sick leave among Japanese employees: a longitudinal study. Int Arch Occup Environ Health. 2006;79(3):213–9. doi: 10.1007/s00420-005-0027-x 16283366

20. Mather L, Bergstrom G, Blom V, Svedberg P. High job demands, job strain, and iso-strain are risk factors for sick leave due to mental disorders: a prospective Swedish twin Study with a 5-year follow-up. J Occup Environ Med. 2015;57(8):858–65. doi: 10.1097/JOM.0000000000000504 26247639

21. de Vries H, Fishta A, Weikert B, Rodriguez Sanchez A, Wegewitz U. Determinants of sickness absence and return to work among employees with common mental disorders: a scoping review. J Occup Rehabil. 2018;28(3):393–417. doi: 10.1007/s10926-017-9730-1 28980107

22. Trybou J, Germonpre S, Janssens H, Casini A, Braeckman L, De Bacquer D, et al. Job-related stress and sickness absence among belgian nurses: a prospective study. J Nurs Sholar. 2014;46(4):292–301.

23. Haveraaen LA, Skarpaas LS, Aas RW. Job demands and decision control predicted return to work: the rapid-RTW cohort study. BMC Public Health. 2017;17(1):154. doi: 10.1186/s12889-016-3942-8 28152995

24. Nieuwenhuijsen K, Bruinvels D, Frings-Dresen M. Psychosocial work environment and stress-related disorders, a systematic review. Occup Med. 2010;60(4):277–86.

25. Sanne B, Mykletun A, Dahl AA, Moen BE, Tell GS. Testing the Job Demand–Control–Support model with anxiety and depression as outcomes: The Hordaland Health Study. Occup Med. 2005;55(6):463–73.

26. Aas RW, Haveraaen L, Sagvaag H, Thørrisen MM. The influence of alcohol consumption on sickness presenteeism and impaired daily activities. The WIRUS screening study. PLOS ONE. 2017;12(10):e0186503. doi: 10.1371/journal.pone.0186503 29040323

27. Nordaune K, Skarpaas LS, Sagvaag H, Haveraaen L, Rimstad S, Kinn LG, et al. Who initiates and organises situations for work-related alcohol use? The WIRUS culture study. Scand J Public Health. 2017;45(8):749–56. doi: 10.1177/1403494817704109 28666393

28. Thørrisen MM, Skogen JC, Aas RW. The associations between employees’ risky drinking and sociodemographics, and implications for intervention needs. BMC Public Health. 2018;18(1):735. doi: 10.1186/s12889-018-5660-x 29898703

29. Skogen JC, Thørrisen MM, Olsen E, Hesse M, Aas RW. Evidence for essential unidimensionality of AUDIT and measurement invariance across gender, age and education. Results from the WIRUS study. Drug Alc Depend. 2019;202:87–92.

30. Thørrisen MM, Bonsaksen T, Hashemi N, Kjeken I, van Mechelen W, Aas RW. Association between alcohol consumption and impaired work performance (presenteeism): a systematic review. BMJ Open. 2019;9(7):e029184. doi: 10.1136/bmjopen-2019-029184 31315869

31. Thørrisen MM, Skogen JC, Kjeken I, Jensen I, Aas RW. Current practices and perceived implementation barriers for working with alcohol prevention in occupational health services: the WIRUS OHS study. Subst Abuse Treat Prev Policy. 2019;14(1):30. doi: 10.1186/s13011-019-0217-2 31242911

32. Eurostat NACE Rev. 2: Statistical classification of economic activities in the European community. 2 ed. Luxembourg: Eurostat; 2008.

33. Karasek R, Theorell T. Healthy work: stress, productivity, and the reconstruction of working life. USA: Basic Books; 1990.

34. Kristensen TS, Borg V, Hannerz H. Socioeconomic status and psychosocial work environment: results from a Danish national study. Scand J Public Health 2002;30(Suppl. 59):41–8.

35. Norwegian Ministry of Children and Families. Gender equality in practice–Equal opportunities for women and men [Likestilling i praksis–Like muligheter for kvinner og menn] (Meld. St. 7 (2015–2016) [White paper no. 7 (2015–2016)]. Oslo, Norway: Norwegian Ministry of Children and Families,; 2015.

36. Sterud T. Work-related psychosocial and mechanical risk factors for work disability: a 3-year follow-up study of the general working population in Norway. Scand J Work Environ Health. 2013;39(5):468–76. doi: 10.5271/sjweh.3359 23529701

37. Bjørk IT, Samdal GB, Hansen BS, Tørstad S, Hamilton GA. Job satisfaction in a Norwegian population of nurses: A questionnaire survey. Int J Nurs Stud. 2007;44(5):747–57. doi: 10.1016/j.ijnurstu.2006.01.002 16504197

38. Costa G. Shift work and health: current problems and preventive actions. Safety Health Work. 2010;1(2):112–23.

39. Harrington JM. Health effects of shift work and extended hours of work. Occup Environ Med. 2001;58(1):68–72.

40. Nena E, Katsaouni M, Steiropoulos P, Theodorou E, Constantinidis TC, Tripsianis G. Effect of shift work on sleep, health, and quality of life of health-care workers. Ind J Occup Environ Med. 2018;22(1):29–34.

41. Knudsen AK, Hotopf M, Skogen JC, Øverland S, Mykletun A. The health status of nonparticipants in a population-based health study: the Hordaland health study. Am J Epidemiol. 2010;172(11):1306–14. doi: 10.1093/aje/kwq257 20843863

42. Field A. Discovering statistics using SPSS. 2 ed. London: Sage Publications; 2005.

43. Schulte PA, Guerin RJ, Schill AL, Bhattacharya A, Cunningham TR, Pandalai SP, Eggerth D, Stephenson CM. Considerations for incorporating "Well-Being" in public policy for workers and workplaces. Am J Public Health 2015;105(8):e31–e44. doi: 10.2105/AJPH.2015.302616 26066933

44. Statistics Norway. Employment, registry based [Sysselsetting, registerbasert] Oslo: Statistics Norway; 2019 [Available from: https://www.ssb.no/regsys].

45. Statistics Norway. Employment, registry based. 1626: State employees by unit and highest completed level of education. Year average 2016–1018 [Sysselsetting, registerbasert. 12626: Ansatte i staten, etter enhet og høyeste fullførte utdanningsnivå. Årsgjennomsnitt 2016–1018] Oslo: Statistics Norway; 2019 [Available from: https://www.ssb.no/statbank/table/12626].