亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Understanding the impact of psychosocial working conditions on workers’ health: we have come a long way, but are we there yet?

工作压力 社会心理的 系统回顾 流行病学 心理健康 心理学 老年学 梅德林 医学 精神科 政治学 病理 法学
作者
Ida E. H. Madsen,Reiner Rugulies
出处
期刊:Scandinavian Journal of Work, Environment & Health [Scaninavian Journal of Work, Environment, and Health]
卷期号:47 (7): 483-487 被引量:13
标识
DOI:10.5271/sjweh.3984
摘要

This issue of the journal includes a meta-review, ie, a systematic review of systematic reviews, summarizing the published evidence on the associations between exposure to adverse psychosocial working conditions and risk of developing diseases or disorders during the past 20 years (1). Although the authors allowed inclusion of reviews reporting results from cross-sectional studies, the majority of the included reviews were restricted to prospective cohort studies – the gold standard method in psychosocial occupational epidemiology. We commend the authors for their succinct summary of the current knowledge on the topic, encompassing this multitude of exposures and outcomes in one single paper. The paper finds that there is consistent evidence of associations between certain psychosocial working conditions (job strain, effort-reward imbalance, job insecurity, long working hours) and certain health conditions (cardiovascular diseases and mental disorders, in particular depression). The paper also identifies the lack of studies concerning numerous other working and health conditions, as elegantly depicted in their figure 1, showing the presence or absence of reviews concerning all combinations of the included exposures and outcomes. The early days of psychosocial occupational epidemiology Compared to other fields of occupational health, research on psychosocial working conditions and health is a relatively recent discipline (2). One of the first studies on the topic was a paper by Friedman et al, published in 1958, reporting increased cholesterol levels and reduced blood clotting time among tax accountants during a period of putative high occupational stress, the annual April 15th tax filing deadline in the United States (3). Curiously, though, this observation did not inspire research on occupational stressors but rather led to the development of the concept of "type A behavior", a behavioral pattern characterized by feelings of time urgency, competitiveness and hostility that became the dominant psychosocial explanation for risk of coronary heart disease in the late 1970s and early 1980s (4). The concept later largely disappeared from the discussion as findings from earlier epidemiological studies could not be replicated (5). In Belgium, Kornitzer and colleagues published a paper in 1975 on the risk of coronary heart disease in employees at two banks, and discussed whether the higher occurrence in one of the banks could be related to work organization (6), a hypothesis which they later examined and corroborated (7). In the 1960s in Sweden, Gardell, Frankenhaeuser and others pioneered both theoretical concepts and empirical research on the role of work under- and overload, participation and alienation for both workplace democracy and workers' health (8-10). This research inspired, among other things, the development of the demand‒control model (job strain model) (11) that was tested in Swedish cohorts from the early 1980s (12, 13). The demand-control model quickly became the dominant approach for understanding the contribution of psychosocial working conditions to risk of cardiovascular disease, but reviews of these studies showed inconsistent results (14, 15). A major advance was made in 2012, when the "Individual-Participant Data Meta-Analysis in Working Populations (IPD-Work) Consortium published pooled estimates from 13 European cohort studies with almost 200 000 participants, showing a prospective association between exposure to job strain and risk of coronary heart disease (16). A key novelty of the IPD approach was to apply harmonized measures of exposures and outcomes in all included cohorts. Subsequent papers from the IPD-Work consortium showed associations between job strain and stroke (17), diabetes (18) and depression (19), between long working hours and coronary heart disease and stroke (20), diabetes (21) and depression (22) and between effort–reward imbalance and coronary heart disease (23). Whereas research on psychosocial work environment and risk of cardiovascular disease has a long history, dating back to the 1980s, research on psychosocial work environment and mental disorders emerged only towards the end of the 1990s, but then rapidly accelerated. When Stansfeld & Candy published the first systematic review and meta-analysis on psychosocial working conditions and common mental disorders in this journal in 2006, they identified only 11 papers (24). In contrast, a recent review by Mikkelsen et al identified 56 papers on the association between psychosocial working conditions and risk of incident clinical depressive disorders (25). The past 20 years of research The meta-review by Niedhammer et al only included reviews with meta-analyses that were published between 2000 and 2020. Given the acceleration of research and the growing number of studies published on the topic, this is a reasonable approach to provide an overview of the current knowledge base. Despite the restriction to the last 20 years, Niedhammer et al identified no less than 72 eligible review studies, a clear indicator of the massive proliferation of studies and the maturation of the research field. Given this vast number of studies, it is timely to ponder what we have learned. For outcomes such as cardiovascular diseases and depression, the included reviews show rather consistently that employees who report certain psychosocial working conditions, in particular job strain, effort–reward imbalance, job insecurity and long working hours, are at increased risk. But how certain can we be that these associations are causal? First, caution is needed because most of the pooled estimates are modest, usually <2.0 and often <1.5. In the presence of numerous other well-established risk factors, such modest risk estimates make residual confounding a crucial issue. This discussion about causality is not new, and many arguments, such as those related to possible bias due to self-reported data, were raised decades ago (26, 27). Despite the massive research efforts, as evident by the number of studies published, it seems some disputes remain unchanged. For example, the above-mentioned recent review by Mikkelsen et al reported numerous associations between psychosocial working conditions and risk of depressive disorders (25), confirming and extending the results of the meta-review (1). However, due to methodological limitations of the literature, the authors did not feel confident to conclude whether psychosocial working conditions are likely or unlikely to cause depressive disorders. So what's next? So how can we move the research field of psychosocial working conditions and health forward? The discussion of causal inference, and how to arrive at it, is not limited to occupational health research. It is a topic of intense debate amongst epidemiologists and philosophers alike, and various approaches exist to establishing causality (28). While some have argued that applying well-defined hypotheses that correspond to potential interventions in combination with certain statistical methods and a counterfactual framework may lead to causal inference (29), others have argued that this approach is overly restrictive and risks limiting the topics that can be researched and the types of evidence that can be considered (30). The latter group proposes that causal claims are arrived at by piecing together bits of evidence from diverse studies, each with their own inherent strengths and weaknesses. Together these studies form a broader picture, like pieces of a puzzle, based on which we can form our judgement. Each study contributes only part of the whole and must be considered in light of the extant knowledge, with a keen eye on ruling out alternative hypotheses. With this in mind, we propose that the identification of alternative hypotheses – in order to rule them out – may be an important next step. Much criticism of psychosocial work environment research has focused on the role of potential biases related to the self-reported nature of exposure measurements in most studies on psychosocial working conditions and health, and calls have been made for studies measuring exposures objectively (26, 27). While the term objective may certainly also be debated (26), we and other research groups have been making steps to meet this challenge by applying non-self-reported exposure measures (31, 32), work unit aggregations (33, 34) or job exposure matrices to measure working conditions (35–37). These measures also have their limitations. Job exposure matrices, for example, are vulnerable to non-differential misclassification, issues related to validation, and are unable to measure day-to-day or between-worker variation within the assigned occupational grouping (38). Consequently these studies should also be seen as only small pieces of the bigger puzzle. But within these limits, they may be considered small steps to rule out the alternative hypothesis of confounding due to reporting bias. Other small steps may be fixed-effects analyses examining intra-individual changes and thereby controlling for time-invariant confounders (39) or studies that analyze the association between onset of exposure and subsequent incident health outcomes (40). Alternative hypotheses may also pertain to the possibility of residual confounding due to factors such as personality, genetics, or life events outside the workplace (41–43). Ruling out these alternative hypotheses – and identifying more – could be considered important next steps for the research field. The issue of causality is not only a technical and somewhat academic discussion. From the viewpoint of those many individuals who believe that they have acquired a health problem due to their psychosocial working conditions, the consequences of this rather academic discussion are very real. More evidence for a causal relationship could result in changes to compensation practices, which would make a tangible difference in the lives of these individuals. At the workplace and societal level, more certainty concerning causality could motivate preventive practices and possibly help prevent the potential adverse health consequences of psychosocial working conditions before they occur – a valuable goal for any public health professional, academic or not. Conflicts of interest The two authors are members of the IPD-Work Consortium and have been involved in several of the reviews that were included in the meta-review. References 1. Niedhammer I, Bertrais S, Witt K. Psychosocial work exposures and health outcomes: a meta-review of 72 literature reviews with meta-analysis. Scand J Work Environ Health. Online First: 28 May 2021. https://doi.org/10.5271/sjweh.3968 2. Gochfeld M. Chronologic history of occupational medicine. J Occup Environ Med. 2005;47(2):96-114. https://doi.org/10.1097/01.jom.0000152917.03649.0e 3. Friedman M, Rosenman RH, Carroll V. Changes in the serum cholesterol and blood clotting time in men subjected to cyclic variation of occupational stress. Circulation. 1958;17(5):852-861. https://doi.org/10.1161/01.CIR.17.5.852 4. The Review Panel on Coronary-Prone Behavior and Coronary Heart Disease. Coronary-prone behavior and coronary heart disease: a critical review. Circulation. 1981;63(6):1199-1215. https://doi.org/10.1161/01.CIR.63.6.1199 5. Myrtek M. Meta-analyses of prospective studies on coronary heart disease, type A personality, and hostility. Int J Cardiol. 2001;79(2-3):245-251. https://doi.org/10.1016/S0167-5273(01)00441-7 6. Kornitzer M, Thilly CH, Vanroux A, Balthazar E. Incidence of ischaemic heart disease in two cohorts of Belgian clerks. Br J Prev Soc Med. 1975;29(2):91-97. https://doi.org/10.1136/jech.29.2.91 7. Kittel F, Kornitzer M, Dramaik M. Coronary heart disease and job stress in two cohorts of bank clerks. Psychother Psychosom. 1980;34(2-3):110-123. https://doi.org/10.1159/000287453 8. Frankenhaeuser M, Gardell B. Underload and overload in working life: outline of a multidisciplinary approach. J Human Stress. 1976;2(3):35-46. https://doi.org/10.1080/0097840X.1976.9936068 9. Gardell B. Scandinavian research on stress in working life. Int J Health Serv. 1982;12(1):31-41. https://doi.org/10.2190/K3DH-0AXW-7DCP-GPFM 10. Johnson JV, Gardell B, Johannson G, editors. The psychosocial work environment work organization, democratization, and health : Essays in memory of Bertil Gardell. Milton Park: Routledge; 1991. 11. Karasek R. Job demands, job decision latitude, and mental strain: Implications for job redesign. Administration Science Quarterly. 1979;24:285-307. https://doi.org/10.2307/2392498 12. Karasek R, Baker D, Marxer F, Ahlbom A, Theorell T. Job decision latitude, job demands, and cardiovascular disease: a prospective study of Swedish men. Am J Public Health. 1981;71(7):694-705. https://doi.org/10.2105/AJPH.71.7.694 13. Alfredsson L, Karasek R, Theorell T. Myocardial infarction risk and psychosocial work environment: an analysis of the male Swedish working force. Soc Sci Med. 1982;16(4):463-467. https://doi.org/10.1016/0277-9536(82)90054-5 14. Kivimäki M, Virtanen M, Elovainio M, Kouvonen A, Väänänen A, Vahtera J. Work stress in the etiology of coronary heart disease--a meta-analysis. Scand J Work Environ Health. 2006;32(6):431-442. https://doi.org/10.5271/sjweh.1049 15. Eller NH, Netterstrøm B, Gyntelberg F, Kristensen TS, Nielsen F, Steptoe A, et al. Work-related psychosocial factors and the development of ischemic heart disease: a systematic review. Cardiol Rev. 2009;17(2):83-97. https://doi.org/10.1097/CRD.0b013e318198c8e9 16. Kivimäki M, Nyberg ST, Batty GD, Fransson EI, Heikkilä K, Alfredsson L, et al. Job strain as a risk factor for coronary heart disease: a collaborative meta-analysis of individual participant data. Lancet. 2012;380(9852):1491-1497. https://doi.org/10.1016/S0140-6736(12)60994-5 17. Fransson EI, Nyberg ST, Heikkilä K, Alfredsson L, Bjorner JB, Borritz M, et al. Job strain and the risk of stroke: an individual-participant data meta-analysis. Stroke. 2015;46(2):557-559. https://doi.org/10.1161/STROKEAHA.114.008019 18. Nyberg ST, Fransson EI, Heikkilä K, Ahola K, Alfredsson L, Bjorner JB, et al. Job strain as a risk factor for type 2 diabetes: a pooled analysis of 124,808 men and women. Diabetes Care. 2014;37(8):2268-2275. https://doi.org/10.2337/dc13-2936 19. Madsen IEH, Nyberg ST, Magnusson Hanson LL, Ferrie JE, Ahola K, Alfredsson L, et al. Job strain as a risk factor for clinical depression: systematic review and meta-analysis with additional individual participant data. Psychol Med. 2017;47(8):1342-1356. https://doi.org/10.1017/S003329171600355X 20. Kivimäki M, Jokela M, Nyberg ST, Singh-Manoux A, Fransson EI, Alfredsson L, et al. Long working hours and risk of coronary heart disease and stroke: a systematic review and meta-analysis of published and unpublished data for 603,838 individuals. Lancet. 2015;386(10005):1739-1746. https://doi.org/10.1016/S0140-6736(15)60295-1 21. Kivimäki M, Virtanen M, Kawachi I, Nyberg ST, Alfredsson L, Batty GD, et al. Long working hours, socioeconomic status, and the risk of incident type 2 diabetes: a meta-analysis of published and unpublished data from 222 120 individuals. Lancet Diabetes Endocrinol. 2015;3(1):27-34. https://doi.org/10.1016/S2213-8587(14)70178-0 22. Virtanen M, Jokela M, Madsen IEH, Magnusson Hanson LL, Lallukka T, Nyberg ST, et al. Long working hours and depressive symptoms: systematic review and meta-analysis of published studies and unpublished individual participant data. Scand J Work Environ Health. 2018;44(3):239-250. https://doi.org/10.5271/sjweh.3712 23. Dragano N, Siegrist J, Nyberg ST, Lunau T, Fransson EI, Alfredsson L, et al. Effort-reward imbalance at work and incident coronary heart disease: a multi-cohort study of 90,164 individuals. Epidemiology. 2017;28(4):619-626. https://doi.org/10.1097/EDE.0000000000000666 24. Stansfeld S, Candy B. Psychosocial work environment and mental health-a meta-analytic review. Scand J Work Environ Health. 2006;32(6):443-462. https://doi.org/10.5271/sjweh.1050 25. Mikkelsen S, Coggon D, Andersen JH, Casey P, Flachs EM, Kolstad HA, et al. Are depressive disorders caused by psychosocial stressors at work? A systematic review with metaanalysis. Eur J Epidemiol. 2021;36(5):479-496. https://doi.org/10.1007/s10654-021-00725-9 26. Frese M, Zapf D. Methodological issues in the study of work stress: Objective vs subjective measurement of work stress and the question of longitudinal studies. In: Cooper CL, Payne R, editors. Causes, coping and consequences of stress at work - Wiley series on studies in occupational stress. Chichester, England: John Wiley & Sons; 1988. p. 375-411. 27. Kasl SV. Measuring job stressors and studying the health impact of the work environment: an epidemiologic commentary. J Occup Health Psychol. 1998;3(4):390-401. https://doi.org/10.1037/1076-8998.3.4.390 28. Beebee H, Hitchcock C, Menzies P, editors. The Oxford handbook of causation. Oxford, UK: Oxford University Press; 2009. Available from: https://www.oxfordhandbooks.com/view//oxfordhb/9780199279739.001.0001/oxfordhb-9780199279739-miscMatter-003. https://doi.org/10.1093/oxfordhb/9780199279739.001.0001 29. VanderWeele TJ, Hernán MA. Causal effects and natural laws: towards a conceptualization of causal counterfactuals for nonmanipulable exposures, with application to the effects of race and sex. In: Berzuini C, Dawid P, Bernardinelli L, editors. Causality: statistical perspectives and applications. Chichester, UK: Wiley; 2012. https://doi.org/10.1002/9781119945710.ch9 30. Vandenbroucke JP, Broadbent A, Pearce N. Causality and causal inference in epidemiology: the need for a pluralistic approach. Int J Epidemiol. 2016;45(6):1776-1786. https://doi.org/10.1093/ije/dyv341 31. Virtanen M, Pentti J, Vahtera J, Ferrie JE, Stansfeld SA, Helenius H, et al. Overcrowding in hospital wards as a predictor of antidepressant treatment among hospital staff. Am J Psychiatry. 2008;165(11):1482-1486. https://doi.org/10.1176/appi.ajp.2008.07121929 32. Griffin JM, Greiner BA, Stansfeld SA, Marmot M. The effect of self-reported and observed job conditions on depression and anxiety symptoms: a comparison of theoretical models. J Occup Health Psychol. 2007;12(4):334-349. https://doi.org/10.1037/1076-8998.12.4.334 33. Bonde JP, Munch-Hansen T, Wieclaw J, Westergaard-Nielsen N, Agerbo E. Psychosocial work environment and antidepressant medication: a prospective cohort study. BMC Public Health. 2009;9:262. https://doi.org/10.1186/1471-2458-9-262 34. Jensen JH, Flachs EM, Török E, Rod NH, Madsen IEH, Rugulies R, et al. Work-unit social capital and incident purchase of psychotropic medications: A longitudinal cohort-study of healthcare workers. J Affect Disord. 2020;276:53-61. https://doi.org/10.1016/j.jad.2020.07.004 35. Madsen IEH, Svane-Petersen AC, Holm A, Burr H, Framke E, Melchior M, et al. Work-related violence and depressive disorder among 955,573 employees followed for 6.99 million person-years. The Danish Work Life Course Cohort study: Work-related violence and depression. J Affect Disord. 2021;288:136-144. https://doi.org/10.1016/j.jad.2021.03.065 36. Rugulies R, Framke E, Sørensen JK, Svane-Petersen AC, Alexanderson K, Bonde JP, et al. Persistent and changing job strain and risk of coronary heart disease. A population-based cohort study of 1.6 million employees in Denmark. Scand J Work Environ Health. 2020;46(4):339-349. https://doi.org/10.5271/sjweh.3891 37. Niedhammer I, Milner A, Geoffroy-Perez B, Coutrot T, LaMontagne AD, Chastang JF. Psychosocial work exposures of the job strain model and cardiovascular mortality in France: results from the STRESSJEM prospective study. Scand J Work Environ Health. 2020;46(5):542-551. https://doi.org/10.5271/sjweh.3902 38. Peters S. Although a valuable method in occupational epidemiology, job-exposure -matrices are no magic fix. Scand J Work Environ Health. 2020;46(3):231-234. https://doi.org/10.5271/sjweh.3894 39. Milner A, Krnjack L, LaMontagne AD. Psychosocial job quality and mental health among young workers: a fixed-effects regression analysis using 13 waves of annual data. Scand J Work Environ Health. 2017;43(1):50-58. https://doi.org/10.5271/sjweh.3608 40. Clark AJ, Salo P, Lange T, Jennum P, Virtanen M, Pentti J, et al. Onset of impaired sleep as a predictor of change in health-related behaviours; analysing observational data as a series of non-randomized pseudo-trials. Int J Epidemiol. 2015;44(3):1027-1037. https://doi.org/10.1093/ije/dyv063 41. Le K, Donnellan MB, Conger R. Personality development at work: workplace conditions, personality changes, and the corresponsive principle. J Pers. 2014;82(1):44-56. https://doi.org/10.1111/jopy.12032 42. Ellis L, Bonin SL. Genetics and occupation-related preferences. Evidence from adoptive and non-adoptive families. Personality and Individual Differences. 2003;35(4):929-937. https://doi.org/10.1016/S0191-8869(02)00309-4 43. Köhler CA, Evangelou E, Stubbs B, Solmi M, Veronese N, Belbasis L, et al. Mapping risk factors for depression across the lifespan: An umbrella review of evidence from meta-analyses and Mendelian randomization studies. J Psychiatr Res. 2018;103:189-207. https://doi.org/10.1016/j.jpsychires.2018.05.020
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Fonseca完成签到 ,获得积分10
1秒前
平日裤子完成签到 ,获得积分10
1秒前
李健应助一剑白采纳,获得10
9秒前
科研通AI2S应助Fonseca采纳,获得10
21秒前
zhl完成签到,获得积分10
22秒前
TWT完成签到,获得积分10
33秒前
52秒前
蔚蓝晴空发布了新的文献求助10
1分钟前
蔚蓝晴空完成签到,获得积分10
1分钟前
自信的傲晴完成签到,获得积分10
1分钟前
Noob_saibot完成签到,获得积分10
1分钟前
Noob_saibot发布了新的文献求助30
2分钟前
衣蝉完成签到 ,获得积分10
2分钟前
脑洞疼应助日拱一卒的蕊采纳,获得10
3分钟前
3分钟前
3分钟前
3分钟前
Frank完成签到,获得积分10
3分钟前
3分钟前
4分钟前
4分钟前
CipherSage应助壮观的雨柏采纳,获得150
4分钟前
希勤发布了新的文献求助10
4分钟前
4分钟前
4分钟前
金玉发布了新的文献求助10
5分钟前
5分钟前
漠北发布了新的文献求助10
5分钟前
5分钟前
5分钟前
6分钟前
LibertyIn发布了新的文献求助10
6分钟前
迷你的靖雁完成签到,获得积分10
6分钟前
传奇完成签到 ,获得积分10
6分钟前
傲娇完成签到,获得积分20
6分钟前
科研螺丝完成签到 ,获得积分10
6分钟前
香蕉觅云应助科研通管家采纳,获得10
7分钟前
hzc应助科研通管家采纳,获得10
7分钟前
7分钟前
7分钟前
高分求助中
Sustainability in Tides Chemistry 2800
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
Rechtsphilosophie 1000
Bayesian Models of Cognition:Reverse Engineering the Mind 888
Le dégorgement réflexe des Acridiens 800
Defense against predation 800
XAFS for Everyone (2nd Edition) 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3133938
求助须知:如何正确求助?哪些是违规求助? 2784836
关于积分的说明 7768641
捐赠科研通 2440205
什么是DOI,文献DOI怎么找? 1297291
科研通“疑难数据库(出版商)”最低求助积分说明 624911
版权声明 600791