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Linking hospital workers’ organisational work environment to depressive symptoms: A mediating effect of effort–reward imbalance? The ORSOSA study
Social Science & Medicine 71 (2010) 534e540
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Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed
Linking hospital workers’ organisational work environment to depressive symptoms: A mediating effect of effortereward imbalance? The ORSOSA studyq Anne Jolivet a, *, Sandrine Caroly b, Virgine Ehlinger a, Michelle Kelly-Irving a, Cyrille Delpierre a, Franck Balducci c, Annie Sobaszek d, Régis De Gaudemaris c, Thierry Lang a a
INSERM, U558, Toulouse F-31300, France Laboratoire PACTE (Politiques Publiques, Action Publique, Territoires), UMR 5194 CNRS, Université Pierre Mendès France, Grenoble, France Laboratoire Environnement et Prédiction de la Santé des Populations (EPSP)-TIMC, UMR CNRS 5525, Grenoble, France d Médecine du Travail et Pathologies Professionnelles, Clinique de Santé Publique, CHRU-Université Lille 2, France b c
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 24 April 2010
Few studies have analysed the association between the organisational work environment and depression in hospital workers and we still have little understanding of how processes in the practice environment are related to depressive disorders. However, individual perception of an imbalance between efforts made and expected rewards has been associated with incident depression. The main goal of this study was to test the hypothesis that some organisational constraints at the work-unit level may be related to depressive symptoms in hospital workers, either directly or through individual perceptions of effortereward imbalance (ERI). In 2006, 3316 female registered nurses and nursing aids working in 190 work units in seven French university hospitals, recruited from the baseline screening of an epidemiological cohort study (the ORSOSA study), responded in 2006 to valid self-report questionnaires (CES-D, ERI). The organisational work environment was assessed with the self-rated Nursing Work Index e Extended Organisation (NWI-EO) aggregated at the work unit level. Multilevel models were used. We found that poor relations between workers within work units were associated with higher CES-D score, independently of perceived ERI. Low level of communication between workers in the unit was associated with individual perceptions of ERI and indirectly associated with depressive symptoms. Understaffing and non-respect of planned days off and vacations were associated with perceived ERI but these organisational constraints were not associated with depressive symptoms. Our study allowed us to identify and quantify organisational factors that have a direct effect on hospital workers’ depressive symptoms, or an indirect effect through perceived ERI. Better understanding of the effect of organisational factors on health through perceived ERI would provide targets for successful interventions. Organisational approaches may be more effective in improving mental health at work and may also have a longer-lasting impact than individual approaches. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: France Hospital workers Mental health Organisational constraints Effortereward imbalance Nurses Work context
Introduction Depressive disorders in hospital workers are a major concern because their prevalence is higher than in the general population of workers (Wall et al., 1997), with resulting high cost implications for q This research was funded by the CNRACL (Caisse Nationale de Retraites des Agents des Collectivités Locales). A. Jolivet held a research scholarship from the Fondation de la Recherche Médicale. The authors thank the other researchers who have been involved in the ORSOSA study: N. Broessel, G. Chattelier, V. Cottel, N. Crowte, P. Diomard, M. Druet-Cabanac, J. Dubuy, P. Gabinski, J. Goddard, F. Herin, I. Kerjean, C. Lecornet, L. Le Guen, E. Lorian, J.M. Soulat, J.M. Tournegros, A. Trichard, M.C. Vignaud. * Corresponding author. Tel.: þ33 5 61 14 59 63; fax: þ33 5 62 26 42 40. E-mail address: [email protected] (A. Jolivet). 0277-9536/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.socscimed.2010.04.003
individuals, employers and society. Depression is the fourth leading cause of disease burden and it is responsible for the greatest non-fatal burden, accounting for almost 12% of all total years lived with disability worldwide in 2000 (Ustun, Ayuso-Mateos, Chatterji, Mathers, & Murray, 2004). Moreover, it is associated with absenteeism and with at-work performance deficits (Lerner & Henke, 2008). There is accumulating evidence that certain characteristics of the psychosocial work environment contribute to the incidence of mental health problems among workers (Bonde, 2008; Michie & Williams, 2003; Stansfeld & Candy, 2006; Tennant, 2001; Wilhelm, Kovess, Rios-Seidel, & Finch, 2004). The most commonly studied models are the demand-control model (Karasek & Theorell, 1990) and the effortereward imbalance (ERI) model (Siegrist,
A. Jolivet et al. / Social Science & Medicine 71 (2010) 534e540
1996). Recent research suggests that organisational justice might also be a predictor of employees’ mental health (Kivimaki, Vahtera, Elovainio, Virtanen, & Siegrist, 2007). Emerging from the social reciprocity theory, the ERI model asserts that ongoing high effort at work in combination with low reward (including money, esteem and career opportunities) lead to distress reactions that result in adverse long-term effects on the physical and mental health of employees (Siegrist et al., 2004). In addition, it is assumed that this process will be intensified with overcommitment (a personality characteristic), such that highly overcommitted employees will respond to ERI with greater strain reactions than less overcommitted employees. Most of the studies which analysed the association between ERI and mental health outcomes have shown a positive relation (Van Vegchel, De Jonge, Bosma, & Schaufeli, 2005) whether they were cross-sectional (De Jonge, Bosma, Peter, & Siegrist, 2000; Hasselhorn, Tackenberg, & Peter, 2004; Niedhammer, Chastang, David, Barouhiel, & Barrandon, 2006; Tsutsumi & Kawakami, 2004) or longitudinal (Kivimaki et al., 2007; Siegrist et al., 2004; Stansfeld, Fuhrer, Shipley, & Marmot, 1999). This model has been confirmed over a wide range of occupations and populations but it is not specific to healthcare workers. In nursing research, a large number of questionnaires have been designed to measure organisational work factors (Bonneterre, Liaudy, Chatellier, Lang, & De Gaudemaris, 2008). A widely-used self-report questionnaire is the RNWI (Revised Nursing Work Index) (Aiken & Patrician, 2000). It assesses the presence of valued organisational traits: nurse autonomy, control over practice, doctor-nurse relationship and organisational support. This tool, derived from research on “magnet hospitals”, was designed to understand how organisational factors such as hospital and workunit characteristics can affect outcomes for nurses and patients. Mental health outcomes have mostly been studied in terms of intention to leave the profession, burnout and job satisfaction (Bonneterre et al., 2008), but few studies have analysed the association between the organisational work environment and depression in nurses. We still have little understanding of how processes in the practice environment are related to outcomes such as depressive disorders. However, individual perception of an imbalance between efforts made and expected rewards is one process that has been associated with incident depression (Kivimaki et al., 2007; Siegrist et al., 2004; Stansfeld et al., 1999). According to the hierarchical conceptual framework of workplace exposure proposed by Macdonald, Harenstam, Warren, and Punnett (2008), which considers that job level hazards (including psychosocial hazards) are nested within the larger organisational context in which work is performed, we hypothesised that some organisational constraints at the workplace may be related to mental health issues through individual perceptions of ERI. This analysis is based on the cross-sectional results of a longitudinal survey carried out in French teaching hospitals among female registered nurses and nursing aids. The main goal was to test the hypothesis that some dimensions of the Nursing Work Index e Extended Organisation (NWI-EO), a scale measuring the organisational work environment at the work unit level, may be related to the depressive symptoms of registered nurses and nursing aids, either directly or through individual perceptions of ERI. Methods Study design The ORSOSA study (Organisation des soins e Santé) is a longitudinal epidemiological survey which was conducted in teaching hospitals in France in 2006 and 2008. It aimed to evaluate the impact of the psychosocial and organisational work environment
535
on registered nurses’ and nursing aids’ health (cardiovascular, mental health and musculoskeletal disorders). The study was approved by the ethics committees of the institutions concerned. A multistage sampling method was used. Teaching hospitals were invited to participate via their occupational medicine departments. Seven hospitals volunteered to participate. Within these hospitals, work units with 20 nurses (registered nurses or nursing aids) and that were not scheduled for closure in the following two years were eligible. A work unit is the smallest unit of organisation in hospitals with a range from 10 to 40 members of staff. Eligible work units were randomly selected after stratification by speciality area to ensure a representative sample of work units from three types of speciality areas: medicine (including geriatric, psychiatric and paediatric units), surgery, and emergency or intensive care units. Ten work units were sampled in each of the three strata in each hospital in order to obtain 210 representative work units. All nurses in the selected work units were then invited to participate. All participants gave their written informed consent. Data were collected in a variety of ways including self-reported questionnaires for nurses, an interview with the head of the work unit, and ergonomic observation of organisational traits. A coordinator in each hospital was trained to give information to the teams, distribute and collect the questionnaires, interview work unit managers and carry out ergonomic observations. The nurses’ questionnaires were anonymous. Finally, 214 work units were included and 4308 nurses completed the first-wave survey (nurses’ inclusion rate was 91.4%). In this study, we carried out cross-sectional analysis of selfreported data from the first wave. Sample used for analysis Male participants were excluded (n ¼ 435) because previous studies have shown that men and women differ in their response patterns to mental health scales (Stansfeld et al., 1999) and stratification was not possible in this study because of a small number of male participants. Furthermore, 311 questionnaires were not analysed because of missing data, and work units with less than 2 registered nurses or less than 2 nursing aids were excluded from analysis (n ¼ 24 work units, 246 nurses). Finally, 3316 questionnaires from 190 work units were analysed. Data collection Depressive symptoms We used the Centre for Epidemiologic Studies-Depression scale (CES-D) which is a self-reported 20-item scale of depressive symptoms experienced in the previous week (Fuhrer & Rouillon, 1989; Radloff, 1977). The total score of the CES-D was used as a continuous measure. The effortereward imbalance (ERI) model The ERI model was assessed using the French version of the standardised questionnaire containing 23 Likert-scaled items (Niedhammer, Siegrist, Landre, Goldberg, & Leclerc, 2000; Siegrist et al., 2004). Effort comprised 6 items referring to the demanding aspects of the work environment. Reward comprised 11 items and included the three subscales of esteem (5 items), job promotion and salary (4 items), and job instability (2 items). The rating procedures and the construction of the score for each scale are described elsewhere (Siegrist et al., 2004). The effort/reward ratio was calculated as follows: effort/reward 11/6. Quartiles of the distribution of the effort/reward ratio were used in order to explore a doseeresponse relationship between effortereward imbalance and depressive symptoms. The short version of the
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overcommitment scale was used to measure the personal component of the model. This subscale comprised six items and measured the inability of the person to withdraw from work obligations and to develop a more distant attitude toward job requirements. Overcommitment was defined by the upper tercile of the distribution among the total female sample (Siegrist et al., 2004). Organisational work environment This was measured with the NWI-EO, the validation of which has been reported elsewhere (submitted for publication). Based on the original 15 items of the RNWI and 19 new items, the NWI-EO, comprising 22 items, was developed and validated in order to take into account new organisational constraints which are accessible to practical preventive interventions within work units in hospitals. A qualitative stage with experts in the field (occupational physicians of hospital staff, ergonomists, psychologists) led to the definition of a certain number of work factors that were not measured by the RNWI-15. The NWI-EO exists in one version destined for nurses and one for nursing aids. The answer model of the RNWI was retained. Each item is evaluated on a 4-point Likert scale. For each dimension, the higher the score, the greater the constraints. Principal components analysis (PCA), based on a randomized split-half of the data, resulted in an eight-factor solution that explained 53% of the common variance. The eight dimensions of the NWI-EO are: (1) Organisation favouring communication between workers in the unit, (2) Support from the senior nurse, (3) Staffing adequacy within the unit to perform work, (4) Good relationships between workers in the unit, (5) Interruptions during tasks, (6) Shared values about work between members in the unit, (7) Support from the administration, (8) Respect of planned days off and vacations. The stability of the factorial structure was confirmed by PCA on the other half-sample as well as by PCA by subgroups (age, gender, occupational group, speciality area, hospital). Internal consistency for 7 of the 8 dimensions (Cronbach > 0.70), and testeretest reliability were satisfactory (Spearman’s rho > 0.6 for 7 of the 8 subscales). The concurrent validity was assessed by comparing individual scores of each dimension of the NWI-EO to external indicators obtained from nurse manager’s interviews (a 55-item questionnaire) and external ergonomic observation. We aggregated the NWI-EO at the work unit level in order to obtain an estimate of the organisational constraints at the work unit level, if intra-unit perceptions and statement were high enough. Work units form relatively homogeneous groups which have their own resources, supervisors and objectives; in addition, sociologists Aiken and Hage (1968) considered that employees in complex organisations could serve as reliable and valid informants concerning the presence of organisational traits. Aggregated measures of the eight dimensions of the NWI-EO were calculated as the mean of individual responses from co-workers in the same work unit. We calculated an aggregated measure separately for registered nurses and nursing aids. Covariates Age, profession (registered nurse or nursing aid), speciality of the work unit (medicine, surgery or emergency/intensive care unit) were systematically introduced in multivariate models. Other potential confounders were tested in preliminary models: employment status (full-time or part-time), and work schedule (working only days or only nights, or days and nights alternately). Data analysis We used intra-class correlation ICC(1,k) as an estimate of reliability of the NWI-EO aggregated at the work unit level. It has been described as an appropriate indicator for deciding whether
aggregated perceptions provide a consistent measure of organisational traits (Glick, 1985). ICC(1,k) was recommended to exceed 0.60 for aggregation of the data (Lake, 2006). Five dimensions of the NWI-EO showed ICC(l,k) higher than 0.60 for both the registered nurses and the nursing aids samples: Organisation favouring communication between workers in the unit, support from the senior nurse, staffing adequacy within the unit to perform work, good relationships between workers in the unit, and respect of planned days off and vacations (Table 1). Therefore, these five dimensions were aggregated at the work unit level. To examine the representativeness of our final sample, we compared distribution of covariates and CES-D score between subjects included in the analysis and those who were not. Comparisons were implemented using the t test for quantitative variables and the chi-square test for qualitative variables. Then we used multilevel models which take into account the existence of data hierarchies and allow examination of the effect of group level and individual variables on individual outcomes, while controlling for non-independence of observations within groups (Goldstein, 1995). We used a three-level model (individual, work unit and hospital). We first conducted bivariate analysis to test covariates associated with the CES-D score. Significant covariates at the 0.2 level were included in multivariate models. To test our hypothesis, we proposed a theoretical framework linking the organisational work environment, ERI and depressive symptoms (Fig. 1). Analysis was therefore conducted in four steps. Firstly, we tested the three main assumptions of the ERI model described in the literature (Van Vegchel et al., 2005): high perceived ERI may increase the risk of depressive symptoms (Fig. 1, arrow 1a), a high level of overcommitment may increase the risk of depressive symptoms (arrow 1b), and lastly employees reporting a high level of ERI and a high level of overcommitment may have an even higher risk of depressive symptoms (arrow 1c). Secondly, we tested the link between the aggregated measures of the NWI-EO at the work unit level and depressive symptoms (arrow 2). Thirdly, we analysed the association between the aggregated measures of the NWI-EO at the work unit level and individual perception of ERI (arrow 3). For this step, the effort/reward ratio was used as a continuous variable (and multiplied by 100 in order to facilitate coefficient interpretation). Finally, we analysed a complete model comprising all the variables and covariates. This procedure in four steps allowed us to test the mediation hypothesis as described by Table 1 Number of items, Cronbach’s alpha and ICC(1,k) at the work unit level by profession for the eight dimensions of the NWI-EO.
1. Organisation favouring communication between workers 2. Support from the senior nurse 3. Staffing adequacy within the unit to perform work 4. Relationships between workers in the unit 5. Interruptions during tasks 6. Shared values about work between members in the unit 7. Support from the administration 8. Respect of planned days off and vacations
Number Cronbach’s ICC(1,k) of items alpha Registered nurses (n ¼ 2228)
Nursing aids (n ¼ 1439)
5
0.66
0.73
0.64
3
0.87
0.87
0.76
2
0.89
0.86
0.83
3
0.71
0.78
0.76
3 2
0.75 0.71
0.70 0.58
0.52 0.54
2
0.77
0.36
0.28
2
0.56
0.76
0.60
A. Jolivet et al. / Social Science & Medicine 71 (2010) 534e540
Fig. 1. Conceptual framework of the pathway linking the organisational work environment to mental health, through individual perceptions of ERI.
Baron and Kenny (1986). Complete mediation is the case in which the initial variable (organisational work environment) no longer affects the outcome (depressive symptoms) after the mediator (ERI) has been controlled. P-values for the fixed effect were derived from the Wald test and the statistical significance level was set at 0.05. All analyses were performed using STATA version 9.0 and random intercept linear models were estimated applying the xtmixed procedure. Results The study sample consisted of 1927 registered nurses and 1389 nursing aids. Analysis of non-respondents showed that our final sample did not differ for age and CES-D score, but more registered nurses than nursing aids were excluded (17.4% vs 9.8%, p < 103, data not shown). The mean age of the final sample was 35.8 years for registered nurses and 40.5 years for nursing aids (Table 2). Registered nurses reported higher efforts, higher ERI, higher overcommitment, and higher scores for four dimensions of the NWI-EO (organisation favouring communication between workers, support from the senior nurse, relationships between workers, support from the administration) than nursing aids. Nursing aids reported greater staffing inadequacy. Mean depression scores were higher for nursing aids (12.8 vs 10.9, p < 103).
537
Variables associated with a higher CES-D score in bivariate analysis were: age 45 years, working during the daytime (only for the nursing aids subgroup), high ERI (with a doseeresponse relationship) and high overcommitment (Table 3). All the aggregated dimensions of the NWI-EO were significantly associated with the CES-D score for both registered nurses and nursing aids. Table 4 presents the regression coefficient estimates from the multilevel models explaining the CES-D score for the total sample. The null model indicates that there was a large level 1 variance for the general intercept between individuals, as could be expected for a health-related variable. Level 2 (work unit) and level 3 (hospital) variances represented 3.5% and 1.1% of the total variance respectively. After controlling for confounding factors, a high level of perceived ERI and a high level of overcommitment were associated with a significantly higher CES-D score (model 1). The interaction between ERI and overcommitment was globally significant (pvalue ¼ 0.03). In this model, total variance decreased by 21.9% compared with the null model, while level 2 and 3 variances decreased by 74.6% and 56.9%, respectively. Associations with CESD score were statistically significant for two of the five aggregated dimensions of the NWI-EO, after adjustment for confounding variables (model 2): low level of communication in the work unit, and bad relationships between workers within the work units. This model decreased the total variance by 3.6% compared with the null model. When the ERI variables and the NWI-EO were both included (model 3), regression coefficient estimates of the dimension “organisation favouring communication between workers” decreased by more than 100%, showing a mediating effect. Regression coefficient estimates of the dimension “relationships between workers within the work units” remained statistically significant in this third model. Results of stratified analysis by profession were similar. Table 5 presents the regression coefficient estimates from the multilevel models explaining the ERI score. The null model indicated that the relative distribution of the random intercept variance at three levels was about 84.7% variation at level 1 (individual), 11.0% variation at level 2 (work unit), and 4.3% variation at level 3
Table 2 Characteristics of the population.
Age (mean SE) (years)
Registered nurses n (%)
Nursing aids n (%)
p-value
35.8 9.2
40.5 9.4
<103
Speciality of work unit
Medicine Surgery Emergency or intensive care unit
633 (32.9) 581 (30.1) 713 (37.0)
543 (39.1) 450 (32.4) 396 (28.5)
<103
Working week
35 h/week < 35 h/week
1453 (75.4) 474 (24.6)
1100 (79.2) 289 (20.8)
0.010
Work schedule
Days only Alternate days/nights or nights only
811 (42.1) 1116 (57.9)
914 (65.8) 475 (34.2)
<103
Effortereward model (mean SE)
Effort score Reward score Effort/reward ratio Overcommitment score
18.6 18.5 0.73 15.7
4.4 4.9 0.22 3.6
16.9 18.3 0.66 14.8
4.4 5.1 0.21 3.7
<103 0.23 <103 <103
NWI-EO (mean SE)
1. 2. 3. 4. 5. 6. 7. 8.
7.6 6.8 8.7 5.9 11.3 6.7 11.7 7.5
2.4 3.4 3.7 2.4 2.9 3.0 3.1 3.4
6.6 6.5 9.5 5.0 10.2 6.6 11.0 7.4
2.3 3.2 3.7 2.6 3.0 3.2 3.4 3.3
<103 0.005 <103 <103 <103 0.32 <103 0.37 <103
Organisation favouring communication Support from the senior nurse Staffing adequacy to perform work Relationships between workers Interruptions during tasks Shared values Support from the administration Respect of planned days off and vacations
CES-D score (mean SE)
10.9 7.9
12.8 8.4
Total
1927 (100)
1389 (100)
SE: standard error.
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Table 3 CES-D score in relation to demographic, psychosocial and organisational variables by profession. Bivariate analysis using linear multilevel models and regression coefficients. Registered nurses Age (reference: <30 years) [30e44] 1.05* 45 years 2.83*** Speciality of work unit (reference: Emergency or ICU) Medicine 0.70y Surgery 0.25
Nursing aids 0.36 2.47*** 0.22 0.60
Working week (reference: part-time) Full-time
0.34
0.40
Schedule (reference: days only) Alternate days/nights or nights only
0.13
1.26*
Effort/reward ratio (reference: 1st quartile low) 2nd Quartile 3rd Quartile 4th Quartile (High)
1.47** 4.38*** 8.48***
1.55** 4.22*** 7.74***
Overcommitment (reference: Low) High
5.95***
6.39***
0.71***
0.63**
0.22** 0.20* 0.40** 0.27*
0.32* 0.22* 0.41** 0.36*
NWI-EO aggregated at level 2 Low level of communication in the work unit Lack of support from the senior nurse Staffing inadequacy to perform work Bad relationships between workers Non-respect of planned days off and vacations
Table 4 CES-D score in relation to psychosocial and organisational variables. Multivariate analysis using multilevel models (n ¼ 3316, 190 work units) and regression coefficients.
***p-value < 103, **0.01 < p < 103, *0.05 < p < 0.01, y0.20 < p < 0.05.
(hospital). In the model analysing the effect of the NWI-EO aggregated at level 2 on individual ERI perceptions (model 4), total variance decreased by 13.8% while level 2 and 3 variances decreased by 79.1% and 31.2%, respectively. After controlling for individual variables (model 5), the three variances were slightly modified. In this last model, three aggregated dimensions of the NWI-EO were significantly associated with higher ERI score: low level of communication in the work unit, staffing inadequacy and non-respect of planned days off and vacations. The first dimension accounted for the greatest decrease in level 2 variance.
Discussion The main finding of this cross-sectional analysis conducted among 3316 registered nurses and nursing aids working in French teaching hospitals was that some organisational constraints in the work unit, measured by the aggregated NWI-EO, were associated with individual depressive symptom scores, either as a direct effect or as a mediated effect through perceived ERI. Results suggested that poor relationships between workers in the work unit were associated with higher depressive symptom scores, regardless of ERI perception. Moreover, we found that low level of communication between workers within work units (concerning patients’ issues, psychological problems encountered by nurses, or organisation of work) was strongly associated with individual perceptions of ERI and indirectly associated with depressive symptoms. We also found that understaffing and the non-respect of planned days off and vacations were associated to a lesser extent with perceived ERI, but these organisational constraints were not associated with depressive symptoms. In addition, our results were concordant with the three hypotheses of the ERI model, as high perceived ERI and high level of overcommitment were related to depressive
Null Model
Model 1 Model 2 Model 3
Fixed effects ERI 1st Quartile (low) 2nd Quartile 3rd Quartile 4th Quartile (high)
0.00 1.15** 3.24*** 4.96***
0.00 1.26** 3.40*** 5.08***
Overcommitment Low High
0.00 4.06***
0.00 4.16***
0.00
0.00
0.49
0.57
0.46
0.56
1.46
1.44
Interaction overcommitment * ERI Low overcommitment and low ERI High overcommitment and medium low ERI High overcommitment and medium high ERI High overcommitment and high ERI NWI-EO (aggregated at level 2) Low level of communication in the work unit Lack of support from the senior nurse Staffing inadequacy to perform work Bad relationships between workers Non-respect of planned days off and vacations Random effects Level 1 (individuals) variance (SE) Level 2 (work unit) variance (SE) Level 3 (hospital) variance (SE) Total variance Relative variation of total variance compared with null model
0.42*
64.21 (1.63) 2.35 (0.65) 0.72 (0.56) 67.29
51.34 (1.30) 1.01 (0.42) 0.18 (0.20) 52.53 21.9%
0.10
0.05
0.03
0.04
0.16*
0.25*
0.26**
0.17
0.09
62.11 (1.57) 1.88 (0.59) 0.86 (0.64) 64.85 3.6%
51.18 (1.30) 1.01 (0.43) 0.24 (0.24) 52.44 22.0%
Model 1 ¼ ERI model (overcommitment þ ERI þ interaction overcommitment/ERI). Model 2 ¼ NWI-EO. Model 3 ¼ ERI model þ NWI-EO. All models were adjusted for age, profession, speciality of the work unit and work schedule. ***p-value < 103, **0.01 < p < 103, *0.05 < p < 0.01.
symptoms, and nurses reporting both high ERI and high level of overcommitment had a higher CES-D score. Limitations and strengths This study presents some limitations. The main limitation is due to the cross-sectional design. We cannot exclude reverse causation where respondents with depressive symptoms may over-report an unfavourable work environment. Some longitudinal studies have provided evidence for reciprocal causal relationships between the work characteristics (including ERI) and mental health, however these studies showed that causal effects were much higher than those for reversed causality (De Jonge et al., 2001; De Lange, Taris, Kompier, Houtman, & Bongers, 2004; Shimazu & de Jonge, 2009). Reverse causation seems all the more unlikely that we used results at the work group level. Another methodological limitation is related to common-method variance, as both the exposure and outcome variables are self-reported and based on individuals’ perceptions,
A. Jolivet et al. / Social Science & Medicine 71 (2010) 534e540 Table 5 ERI score in relation to organisational variables. Multivariate analysis using linear multilevel models and regression coefficients. Total sample (n ¼ 3316) Null Model Fixed effects NWI-EO Low level of communication in the work unit Lack of support from the senior nurse Staffing inadequacy to perform work Bad relationships between workers Non-respect of planned days off and vacations Random effects Level 1 (individuals) variance (SE) Level 2 (work unit) variance (SE) Level 3 (hospital) variance (SE) Total variance Relative variation of total variance compared with null model
Model 4
4.35*** 0.20 0.98*** 0.70** 0.52
411.505 (10.4) 53.59 (8.19) 20.64 (13.70) 485.28
393.11 (9.94) 11.19 (3.59) 14.18 (9.01) 418.48 13.8%
Model 5
3.30*** 0.27 1.38*** 0.31 0.59*
387.20 (9.80) 12.94 (3.80) 13.45 (8.74) 413.59 14.8%
Model 4:NWI-EO (unadjusted). Model 5:NWI-EO (adjusted for age, profession, speciality of the work unit, work week, work schedule). ***p-value < 103; **0.01 < p < 103; *0.05 < p < 0.01.
which can lead to inflated associations. However aggregating individual responses up to a work group level as been suggested as an alternative to limit this bias in organisational research (Kawachi, 2006). Another unlikely source of bias is a selection bias due to the elimination of 557 eligible subjects because of missing values or because they were in work units comprising less than two registered nurses and two nursing aids. Hospitals participated voluntarily and the study sample was female only. Therefore interpretation of the findings can only be made for women. Also, our findings cannot be generalised to other occupational groups in hospitals. The use of aggregated measures of the organisational work environment at the work unit level was limited to five dimensions of the NWI-EO because ICC(1,k) was lower than 0.60, which indicates heterogeneity of nurses’ perceptions within work units. Lastly, past medical history of depression, stressful life events and stressful factors in home life were not available in this study. These limitations are balanced by several strengths. Firstly, the participation rate was high. Secondly, we used random sampling of the work units. Thirdly, we used a multilevel model which takes into account the data hierarchies and the non-independence of observations within groups. Fourthly, we used aggregated data which allowed us to test a contextual effect of organisational factors on individual outcomes and to cancel out the impact of differences in personal perceptions. Finally, the “communication” and “relation” dimensions of the NWI-EO both benefit from a good concurrent validity: for registered nurses, NWI-EO scores for the communication possibilities dimension were significantly higher in work units where shift handovers were informal vs formal (following structured steps). For nursing aids, NWI-EO scores for relationships within the work unit were significantly higher when there were conflicts which disrupted organisation in the unit as assessed by the nurse manager interview.
Interpretation of the results Our findings with respect to the ERI model are in agreement with those of previous cross-sectional or longitudinal studies, showing that perception of effortereward imbalance influences
539
depressive disorders (Kivimaki et al., 2007; Siegrist et al., 2004; Stansfeld et al., 1999). However, associations between overcommitment and depressive symptoms on the one hand and between overcommitment/ERI interaction and depressive symptoms on the other hand are less consistent in the literature (Van Vegchel, 2005). Few nursing research studies have analysed the association between depression and organisational factors in hospitals. A cross-sectional study among 343 female employees from a large Danish hospital (patient care workers and laboratory technicians) showed that high levels of demand at work, low meaning of work and low social support at work (from colleagues and supervisors) were significantly associated with poorer mental health (Aust, Rugulies, Skakon, Scherzer, & Jensen, 2007). A cross-sectional survey carried out among the employees of two Spanish hospitals (n ¼ 313) showed that high psychological demands and low social support were associated with poor mental health (Escriba-Aguir & Tenias-Burillo, 2004). Lastly, a case-control study among 128 English healthcare professionals showed that employees presenting minor psychiatric disorders reported greater lack of management support and more role conflicts (Weinberg & Creed, 2000). There is abundant literature concerning intention to leave the profession, burnout and job satisfaction. A systematic review of published studies conducted to assess the association between organisational factors and burnout underlined the importance of support by supervisors, doctor/nurse relations, support by the administration and nurse staffing (Gershon et al., 2007). Moreover, studies which aimed to analyse the combined effect of both the ERI model and the Karasek model reported that perception of ERI and social support had an independent effect on health (Niedhammer et al., 2006; Stansfeld & Candy, 2006). Our analysis showed that poor team relations at the work unit level were associated with higher depressive scores regardless of ERI perception, but we found no relation with senior nurse support. We hypothesised that organisational factors within the work unit measured by the aggregated NWI-EO could have an impact on depressive symptoms through individual ERI perception. Our results suggest that organisational constraints in the work unit have a strong contextual effect on individual perceptions of ERI, as the differences between units in the level of ERI perceived by their nurses and nursing aids seem to be mainly explained by differences in the level of organisational constraints between these units. In the literature, we have found no epidemiological studies which suggested such mediation pathways between organisational constraints in the workplace and mental health through ERI perceptions. However, an intervention study supports our assumption. Bourbonnais, Brisson, Vinet, Vezina, and Lower (2006) developed a participative intervention among care providers in an acute care hospital in Quebec using a quasi-experimental design with a control group. Qualitative methods were used to identify adverse conditions, then specific solutions related to teamwork, team spirit, staffing processes, work organisation, training, communication, and ergonomy were implemented in the experimental group. After one year, results suggested that the intervention had a positive effect in the experimental group (Bourbonnais, Brisson, Vinet, Vezina, Abdous, et al., 2006) by reducing adverse psychosocial work factors, among them ERI which was considered as an intermediate effect, and by improving mental health outcomes, considered as the final effect of the intervention. Interventions mostly target individuals rather than work organisation by implementing stress management programmes, while many authors suggest that organisational approaches are more effective and have more important, longer-lasting effects than individual approaches (Kompier & Kristensen, 2000). Intervention studies based on the ERI model are limited and focused mainly on individual
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employees. Nevertheless, work environment improvement approaches according to this model have been proposed (Tsutsumi & Kawakami, 2004). They combine behavioural modifications but apply mainly socio-environmental and organisational strategies. Conclusion Our study and our theoretical model allowed us to identify and quantify organisational factors that are associated with mental health either directly or indirectly through perceived ERI. Such a mediating effect of organisational factors on health through ERI perceptions would provide one of the mechanisms through which interventions based on the ERI theory could be successful. Analysis of the prospective data of the ORSOSA study and the combination of multiple measurements of organisational factors, such as external assessments of organisational constraints in work units and individual data, will assist in drawing conclusions about causal relationships. References Aiken, L. H., & Patrician, P. A. (2000). Measuring organizational traits of hospitals: the revised nursing work index. Nursing Research, 49, 146e153. Aiken, M., & Hage, J. (1968). Organizational interdependence and intraorganizational structure. American Journal of Sociology, 33, 912e930. Aust, B., Rugulies, R., Skakon, J., Scherzer, T., & Jensen, C. (2007). Psychosocial work environment of hospital workers: validation of a comprehensive assessment scale. International Journal of Nursing Studies, 44, 814e825. Baron, R. M., & Kenny, D. A. (1986). The moderatoremediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173e1182. Bonde, J. P. (2008). Psychosocial factors at work and risk of depression: a systematic review of the epidemiological evidence. Occupational and Environmental Medicine, 65, 438e445. Bonneterre, V., Liaudy, S., Chatellier, G., Lang, T., & De Gaudemaris, R. (2008). Reliability, validity, and health issues arising from questionnaires used to measure Psychosocial and Organizational Work Factors (POWFs) among hospital nurses: a critical review. Journal of Nursing Measurement, 16, 207e230. Bourbonnais, R., Brisson, C., Vinet, A., Vezina, M., Abdous, B., & Gaudet, M. (2006). Effectiveness of a participative intervention on psychosocial work factors to prevent mental health problems in a hospital setting. Occupational and Environmental Medicine, 63, 335e342. Bourbonnais, R., Brisson, C., Vinet, A., Vezina, M., & Lower, A. (2006). Development and implementation of a participative intervention to improve the psychosocial work environment and mental health in an acute care hospital. Occupational and Environmental Medicine, 63, 326e334. De Jonge, J., Bosma, H., Peter, R., & Siegrist, J. (2000). Job strain, effortereward imbalance and employee well-being: a large-scale cross-sectional study. Social Science & Medicine, 50, 1317e1327. De Jonge, J., Dormann, C., Janssen, P. P. M., Dollard, M. F., Landeweerd, J. A., & Nijhuis, F. J. N. (2001). Testing reciprocal relationships between job characteristics and psychological well-being: a cross-lagged structural equation model. Journal of Occupational and Organizational Psychology, 74, 29e46. De Lange, A., Taris, T., Kompier, M., Houtman, I., & Bongers, P. (2004). The relationships between work characteristics and mental health: examining normal, reversed and reciprocal relationships in a 4-wave study. Work & Stress, 18, 149e166. Escriba-Aguir, V., & Tenias-Burillo, J. M. (2004). Psychological well-being among hospital personnel: the role of family demands and psychosocial work environment. International Archives of Occupational and Environmental Health, 77, 401e408. Fuhrer, R., & Rouillon, F. (1989). La version française de l’échelle CES-D: description et traduction de l’échelle d’auto-évaluation. Psychiatry and Psychobiology, 4, 163e166. Gershon, R. R., Stone, P. W., Zeltser, M., Faucett, J., MacDavitt, K., & Chou, S. S. (2007). Organizational climate and nurse health outcomes in the United States: a systematic review. Industrial Health, 45, 622e636.
Glick, W. H. (1985). Conceptualizing and measuring organizational and psychological climate: pitfalls in multilevel research. Academy of Management Review, 10, 601e616. Goldstein, H. (1995). Multilevel statistical models. London: Edward Arnold. Hasselhorn, H. M., Tackenberg, P., & Peter, R. (2004). Effortereward imbalance among nurses in stable countries and in countries in transition. International Journal of Occupational and Environmental Health, 10, 401e408. Karasek, R., & Theorell, T. (1990). Healthy work: Stress, productivity and the reconstruction of working life. New York: Basic Books. Kawachi, I. (2006). Injustice at work and health: causation or correlation? Occupational and Environmental Medicine, 63, 578e579. Kivimaki, M., Vahtera, J., Elovainio, M., Virtanen, M., & Siegrist, J. (2007). Effortereward imbalance, procedural injustice and relational injustice as psychosocial predictors of health: complementary or redundant models? Occupational and Environmental Medicine, 64, 659e665. Kompier, M., & Kristensen, T. S. (2000). Organizational work stress interventions in a theoretical, methodological and practical context. In J. Dunham (Ed.), Stress in the workplace: Past, present and future (pp. 164e190). London/Philadelphia: Whurr Publishers. Lake, E. T. (2006). Multilevel models in health outcomes research. Part I: theory, design, and measurement. Applied Nursing Research, 19, 51e53. Lerner, D., & Henke, R. M. (2008). What does research tell us about depression, job performance, and work productivity? Journal of Occupational and Environmental Medicine, 50, 401e410. Macdonald, L. A., Harenstam, A., Warren, N. D., & Punnett, L. (2008). Incorporating work organisation into occupational health research: an invitation for dialogue. Occupational and Environmental Medicine, 65, 1e3. Michie, S., & Williams, S. (2003). Reducing work related psychological ill health and sickness absence: a systematic literature review. Occupational and Environmental Medicine, 60, 3e9. Niedhammer, I., Chastang, J. F., David, S., Barouhiel, L., & Barrandon, G. (2006). Psychosocial work environment and mental health: job-strain and effortereward imbalance models in a context of major organizational changes. International Journal of Occupational and Environmental Health, 12, 111e119. Niedhammer, I., Siegrist, J., Landre, M. F., Goldberg, M., & Leclerc, A. (2000). Psychometric properties of the French version of the effortereward imbalance model. Revue d’Epidemiologie et de Sante Publique, 48, 419e437. Radloff, L. (1977). The CES-D Scale: a self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385. Shimazu, A., & de Jonge, J. (2009). Reciprocal relations between effortereward imbalance at work and adverse health: a three-wave panel survey. Social Science & Medicine, 68, 60e68. Siegrist, J. (1996). Adverse health effects of high-effort/low-reward conditions. Journal of Occupational Health Psychology, 1, 27e41. Siegrist, J., Starke, D., Chandola, T., Godin, I., Marmot, M., Niedhammer, I., et al. (2004). The measurement of effortereward imbalance at work: European comparisons. Social Science & Medicine, 58, 1483e1499. Stansfeld, S. A., Fuhrer, R., Shipley, M. J., & Marmot, M. G. (1999). Work characteristics predict psychiatric disorder: prospective results from the Whitehall II Study. Occupational and Environmental Medicine, 56, 302e307. Stansfeld, S., & Candy, B. (2006). Psychosocial work environment and mental health e a meta-analytic review. Scandinavian Journal of Work, Environment & Health, 32, 443e462. Tennant, C. (2001). Work-related stress and depressive disorders. Journal of Psychosomatic Research, 51, 697e704. Tsutsumi, A., & Kawakami, N. (2004). A review of empirical studies on the model of effortereward imbalance at work: reducing occupational stress by implementing a new theory. Social Science & Medicine, 59, 2335e2359. Ustun, T. B., Ayuso-Mateos, J. L., Chatterji, S., Mathers, C., & Murray, C. J. (2004). Global burden of depressive disorders in the year 2000. British Journal of Psychiatry, 184, 386e392. Van Vegchel, N., De Jonge, J., Bosma, H., & Schaufeli, W. (2005). Reviewing the effortereward imbalance model: drawing up the balance of 45 empirical studies. Social Science & Medicine, 60, 1117e1131. Wall, T. D., Bolden, R. I., Borrill, C. S., Carter, A. J., Golya, D. A., Hardy, G. E., et al. (1997). Minor psychiatric disorder in NHS trust staff: occupational and gender differences. British Journal of Psychiatry, 171, 519e523. Weinberg, A., & Creed, F. (2000). Stress and psychiatric disorder in healthcare professionals and hospital staff. Lancet, 355, 533e537. Wilhelm, K., Kovess, V., Rios-Seidel, C., & Finch, A. (2004). Work and mental health. Social Psychiatry and Psychiatric Epidemiology, 39, 866e873.
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Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed
Linking hospital workers’ organisational work environment to depressive symptoms: A mediating effect of effortereward imbalance? The ORSOSA studyq Anne Jolivet a, *, Sandrine Caroly b, Virgine Ehlinger a, Michelle Kelly-Irving a, Cyrille Delpierre a, Franck Balducci c, Annie Sobaszek d, Régis De Gaudemaris c, Thierry Lang a a
INSERM, U558, Toulouse F-31300, France Laboratoire PACTE (Politiques Publiques, Action Publique, Territoires), UMR 5194 CNRS, Université Pierre Mendès France, Grenoble, France Laboratoire Environnement et Prédiction de la Santé des Populations (EPSP)-TIMC, UMR CNRS 5525, Grenoble, France d Médecine du Travail et Pathologies Professionnelles, Clinique de Santé Publique, CHRU-Université Lille 2, France b c
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 24 April 2010
Few studies have analysed the association between the organisational work environment and depression in hospital workers and we still have little understanding of how processes in the practice environment are related to depressive disorders. However, individual perception of an imbalance between efforts made and expected rewards has been associated with incident depression. The main goal of this study was to test the hypothesis that some organisational constraints at the work-unit level may be related to depressive symptoms in hospital workers, either directly or through individual perceptions of effortereward imbalance (ERI). In 2006, 3316 female registered nurses and nursing aids working in 190 work units in seven French university hospitals, recruited from the baseline screening of an epidemiological cohort study (the ORSOSA study), responded in 2006 to valid self-report questionnaires (CES-D, ERI). The organisational work environment was assessed with the self-rated Nursing Work Index e Extended Organisation (NWI-EO) aggregated at the work unit level. Multilevel models were used. We found that poor relations between workers within work units were associated with higher CES-D score, independently of perceived ERI. Low level of communication between workers in the unit was associated with individual perceptions of ERI and indirectly associated with depressive symptoms. Understaffing and non-respect of planned days off and vacations were associated with perceived ERI but these organisational constraints were not associated with depressive symptoms. Our study allowed us to identify and quantify organisational factors that have a direct effect on hospital workers’ depressive symptoms, or an indirect effect through perceived ERI. Better understanding of the effect of organisational factors on health through perceived ERI would provide targets for successful interventions. Organisational approaches may be more effective in improving mental health at work and may also have a longer-lasting impact than individual approaches. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: France Hospital workers Mental health Organisational constraints Effortereward imbalance Nurses Work context
Introduction Depressive disorders in hospital workers are a major concern because their prevalence is higher than in the general population of workers (Wall et al., 1997), with resulting high cost implications for q This research was funded by the CNRACL (Caisse Nationale de Retraites des Agents des Collectivités Locales). A. Jolivet held a research scholarship from the Fondation de la Recherche Médicale. The authors thank the other researchers who have been involved in the ORSOSA study: N. Broessel, G. Chattelier, V. Cottel, N. Crowte, P. Diomard, M. Druet-Cabanac, J. Dubuy, P. Gabinski, J. Goddard, F. Herin, I. Kerjean, C. Lecornet, L. Le Guen, E. Lorian, J.M. Soulat, J.M. Tournegros, A. Trichard, M.C. Vignaud. * Corresponding author. Tel.: þ33 5 61 14 59 63; fax: þ33 5 62 26 42 40. E-mail address: [email protected] (A. Jolivet). 0277-9536/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.socscimed.2010.04.003
individuals, employers and society. Depression is the fourth leading cause of disease burden and it is responsible for the greatest non-fatal burden, accounting for almost 12% of all total years lived with disability worldwide in 2000 (Ustun, Ayuso-Mateos, Chatterji, Mathers, & Murray, 2004). Moreover, it is associated with absenteeism and with at-work performance deficits (Lerner & Henke, 2008). There is accumulating evidence that certain characteristics of the psychosocial work environment contribute to the incidence of mental health problems among workers (Bonde, 2008; Michie & Williams, 2003; Stansfeld & Candy, 2006; Tennant, 2001; Wilhelm, Kovess, Rios-Seidel, & Finch, 2004). The most commonly studied models are the demand-control model (Karasek & Theorell, 1990) and the effortereward imbalance (ERI) model (Siegrist,
A. Jolivet et al. / Social Science & Medicine 71 (2010) 534e540
1996). Recent research suggests that organisational justice might also be a predictor of employees’ mental health (Kivimaki, Vahtera, Elovainio, Virtanen, & Siegrist, 2007). Emerging from the social reciprocity theory, the ERI model asserts that ongoing high effort at work in combination with low reward (including money, esteem and career opportunities) lead to distress reactions that result in adverse long-term effects on the physical and mental health of employees (Siegrist et al., 2004). In addition, it is assumed that this process will be intensified with overcommitment (a personality characteristic), such that highly overcommitted employees will respond to ERI with greater strain reactions than less overcommitted employees. Most of the studies which analysed the association between ERI and mental health outcomes have shown a positive relation (Van Vegchel, De Jonge, Bosma, & Schaufeli, 2005) whether they were cross-sectional (De Jonge, Bosma, Peter, & Siegrist, 2000; Hasselhorn, Tackenberg, & Peter, 2004; Niedhammer, Chastang, David, Barouhiel, & Barrandon, 2006; Tsutsumi & Kawakami, 2004) or longitudinal (Kivimaki et al., 2007; Siegrist et al., 2004; Stansfeld, Fuhrer, Shipley, & Marmot, 1999). This model has been confirmed over a wide range of occupations and populations but it is not specific to healthcare workers. In nursing research, a large number of questionnaires have been designed to measure organisational work factors (Bonneterre, Liaudy, Chatellier, Lang, & De Gaudemaris, 2008). A widely-used self-report questionnaire is the RNWI (Revised Nursing Work Index) (Aiken & Patrician, 2000). It assesses the presence of valued organisational traits: nurse autonomy, control over practice, doctor-nurse relationship and organisational support. This tool, derived from research on “magnet hospitals”, was designed to understand how organisational factors such as hospital and workunit characteristics can affect outcomes for nurses and patients. Mental health outcomes have mostly been studied in terms of intention to leave the profession, burnout and job satisfaction (Bonneterre et al., 2008), but few studies have analysed the association between the organisational work environment and depression in nurses. We still have little understanding of how processes in the practice environment are related to outcomes such as depressive disorders. However, individual perception of an imbalance between efforts made and expected rewards is one process that has been associated with incident depression (Kivimaki et al., 2007; Siegrist et al., 2004; Stansfeld et al., 1999). According to the hierarchical conceptual framework of workplace exposure proposed by Macdonald, Harenstam, Warren, and Punnett (2008), which considers that job level hazards (including psychosocial hazards) are nested within the larger organisational context in which work is performed, we hypothesised that some organisational constraints at the workplace may be related to mental health issues through individual perceptions of ERI. This analysis is based on the cross-sectional results of a longitudinal survey carried out in French teaching hospitals among female registered nurses and nursing aids. The main goal was to test the hypothesis that some dimensions of the Nursing Work Index e Extended Organisation (NWI-EO), a scale measuring the organisational work environment at the work unit level, may be related to the depressive symptoms of registered nurses and nursing aids, either directly or through individual perceptions of ERI. Methods Study design The ORSOSA study (Organisation des soins e Santé) is a longitudinal epidemiological survey which was conducted in teaching hospitals in France in 2006 and 2008. It aimed to evaluate the impact of the psychosocial and organisational work environment
535
on registered nurses’ and nursing aids’ health (cardiovascular, mental health and musculoskeletal disorders). The study was approved by the ethics committees of the institutions concerned. A multistage sampling method was used. Teaching hospitals were invited to participate via their occupational medicine departments. Seven hospitals volunteered to participate. Within these hospitals, work units with 20 nurses (registered nurses or nursing aids) and that were not scheduled for closure in the following two years were eligible. A work unit is the smallest unit of organisation in hospitals with a range from 10 to 40 members of staff. Eligible work units were randomly selected after stratification by speciality area to ensure a representative sample of work units from three types of speciality areas: medicine (including geriatric, psychiatric and paediatric units), surgery, and emergency or intensive care units. Ten work units were sampled in each of the three strata in each hospital in order to obtain 210 representative work units. All nurses in the selected work units were then invited to participate. All participants gave their written informed consent. Data were collected in a variety of ways including self-reported questionnaires for nurses, an interview with the head of the work unit, and ergonomic observation of organisational traits. A coordinator in each hospital was trained to give information to the teams, distribute and collect the questionnaires, interview work unit managers and carry out ergonomic observations. The nurses’ questionnaires were anonymous. Finally, 214 work units were included and 4308 nurses completed the first-wave survey (nurses’ inclusion rate was 91.4%). In this study, we carried out cross-sectional analysis of selfreported data from the first wave. Sample used for analysis Male participants were excluded (n ¼ 435) because previous studies have shown that men and women differ in their response patterns to mental health scales (Stansfeld et al., 1999) and stratification was not possible in this study because of a small number of male participants. Furthermore, 311 questionnaires were not analysed because of missing data, and work units with less than 2 registered nurses or less than 2 nursing aids were excluded from analysis (n ¼ 24 work units, 246 nurses). Finally, 3316 questionnaires from 190 work units were analysed. Data collection Depressive symptoms We used the Centre for Epidemiologic Studies-Depression scale (CES-D) which is a self-reported 20-item scale of depressive symptoms experienced in the previous week (Fuhrer & Rouillon, 1989; Radloff, 1977). The total score of the CES-D was used as a continuous measure. The effortereward imbalance (ERI) model The ERI model was assessed using the French version of the standardised questionnaire containing 23 Likert-scaled items (Niedhammer, Siegrist, Landre, Goldberg, & Leclerc, 2000; Siegrist et al., 2004). Effort comprised 6 items referring to the demanding aspects of the work environment. Reward comprised 11 items and included the three subscales of esteem (5 items), job promotion and salary (4 items), and job instability (2 items). The rating procedures and the construction of the score for each scale are described elsewhere (Siegrist et al., 2004). The effort/reward ratio was calculated as follows: effort/reward 11/6. Quartiles of the distribution of the effort/reward ratio were used in order to explore a doseeresponse relationship between effortereward imbalance and depressive symptoms. The short version of the
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overcommitment scale was used to measure the personal component of the model. This subscale comprised six items and measured the inability of the person to withdraw from work obligations and to develop a more distant attitude toward job requirements. Overcommitment was defined by the upper tercile of the distribution among the total female sample (Siegrist et al., 2004). Organisational work environment This was measured with the NWI-EO, the validation of which has been reported elsewhere (submitted for publication). Based on the original 15 items of the RNWI and 19 new items, the NWI-EO, comprising 22 items, was developed and validated in order to take into account new organisational constraints which are accessible to practical preventive interventions within work units in hospitals. A qualitative stage with experts in the field (occupational physicians of hospital staff, ergonomists, psychologists) led to the definition of a certain number of work factors that were not measured by the RNWI-15. The NWI-EO exists in one version destined for nurses and one for nursing aids. The answer model of the RNWI was retained. Each item is evaluated on a 4-point Likert scale. For each dimension, the higher the score, the greater the constraints. Principal components analysis (PCA), based on a randomized split-half of the data, resulted in an eight-factor solution that explained 53% of the common variance. The eight dimensions of the NWI-EO are: (1) Organisation favouring communication between workers in the unit, (2) Support from the senior nurse, (3) Staffing adequacy within the unit to perform work, (4) Good relationships between workers in the unit, (5) Interruptions during tasks, (6) Shared values about work between members in the unit, (7) Support from the administration, (8) Respect of planned days off and vacations. The stability of the factorial structure was confirmed by PCA on the other half-sample as well as by PCA by subgroups (age, gender, occupational group, speciality area, hospital). Internal consistency for 7 of the 8 dimensions (Cronbach > 0.70), and testeretest reliability were satisfactory (Spearman’s rho > 0.6 for 7 of the 8 subscales). The concurrent validity was assessed by comparing individual scores of each dimension of the NWI-EO to external indicators obtained from nurse manager’s interviews (a 55-item questionnaire) and external ergonomic observation. We aggregated the NWI-EO at the work unit level in order to obtain an estimate of the organisational constraints at the work unit level, if intra-unit perceptions and statement were high enough. Work units form relatively homogeneous groups which have their own resources, supervisors and objectives; in addition, sociologists Aiken and Hage (1968) considered that employees in complex organisations could serve as reliable and valid informants concerning the presence of organisational traits. Aggregated measures of the eight dimensions of the NWI-EO were calculated as the mean of individual responses from co-workers in the same work unit. We calculated an aggregated measure separately for registered nurses and nursing aids. Covariates Age, profession (registered nurse or nursing aid), speciality of the work unit (medicine, surgery or emergency/intensive care unit) were systematically introduced in multivariate models. Other potential confounders were tested in preliminary models: employment status (full-time or part-time), and work schedule (working only days or only nights, or days and nights alternately). Data analysis We used intra-class correlation ICC(1,k) as an estimate of reliability of the NWI-EO aggregated at the work unit level. It has been described as an appropriate indicator for deciding whether
aggregated perceptions provide a consistent measure of organisational traits (Glick, 1985). ICC(1,k) was recommended to exceed 0.60 for aggregation of the data (Lake, 2006). Five dimensions of the NWI-EO showed ICC(l,k) higher than 0.60 for both the registered nurses and the nursing aids samples: Organisation favouring communication between workers in the unit, support from the senior nurse, staffing adequacy within the unit to perform work, good relationships between workers in the unit, and respect of planned days off and vacations (Table 1). Therefore, these five dimensions were aggregated at the work unit level. To examine the representativeness of our final sample, we compared distribution of covariates and CES-D score between subjects included in the analysis and those who were not. Comparisons were implemented using the t test for quantitative variables and the chi-square test for qualitative variables. Then we used multilevel models which take into account the existence of data hierarchies and allow examination of the effect of group level and individual variables on individual outcomes, while controlling for non-independence of observations within groups (Goldstein, 1995). We used a three-level model (individual, work unit and hospital). We first conducted bivariate analysis to test covariates associated with the CES-D score. Significant covariates at the 0.2 level were included in multivariate models. To test our hypothesis, we proposed a theoretical framework linking the organisational work environment, ERI and depressive symptoms (Fig. 1). Analysis was therefore conducted in four steps. Firstly, we tested the three main assumptions of the ERI model described in the literature (Van Vegchel et al., 2005): high perceived ERI may increase the risk of depressive symptoms (Fig. 1, arrow 1a), a high level of overcommitment may increase the risk of depressive symptoms (arrow 1b), and lastly employees reporting a high level of ERI and a high level of overcommitment may have an even higher risk of depressive symptoms (arrow 1c). Secondly, we tested the link between the aggregated measures of the NWI-EO at the work unit level and depressive symptoms (arrow 2). Thirdly, we analysed the association between the aggregated measures of the NWI-EO at the work unit level and individual perception of ERI (arrow 3). For this step, the effort/reward ratio was used as a continuous variable (and multiplied by 100 in order to facilitate coefficient interpretation). Finally, we analysed a complete model comprising all the variables and covariates. This procedure in four steps allowed us to test the mediation hypothesis as described by Table 1 Number of items, Cronbach’s alpha and ICC(1,k) at the work unit level by profession for the eight dimensions of the NWI-EO.
1. Organisation favouring communication between workers 2. Support from the senior nurse 3. Staffing adequacy within the unit to perform work 4. Relationships between workers in the unit 5. Interruptions during tasks 6. Shared values about work between members in the unit 7. Support from the administration 8. Respect of planned days off and vacations
Number Cronbach’s ICC(1,k) of items alpha Registered nurses (n ¼ 2228)
Nursing aids (n ¼ 1439)
5
0.66
0.73
0.64
3
0.87
0.87
0.76
2
0.89
0.86
0.83
3
0.71
0.78
0.76
3 2
0.75 0.71
0.70 0.58
0.52 0.54
2
0.77
0.36
0.28
2
0.56
0.76
0.60
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Fig. 1. Conceptual framework of the pathway linking the organisational work environment to mental health, through individual perceptions of ERI.
Baron and Kenny (1986). Complete mediation is the case in which the initial variable (organisational work environment) no longer affects the outcome (depressive symptoms) after the mediator (ERI) has been controlled. P-values for the fixed effect were derived from the Wald test and the statistical significance level was set at 0.05. All analyses were performed using STATA version 9.0 and random intercept linear models were estimated applying the xtmixed procedure. Results The study sample consisted of 1927 registered nurses and 1389 nursing aids. Analysis of non-respondents showed that our final sample did not differ for age and CES-D score, but more registered nurses than nursing aids were excluded (17.4% vs 9.8%, p < 103, data not shown). The mean age of the final sample was 35.8 years for registered nurses and 40.5 years for nursing aids (Table 2). Registered nurses reported higher efforts, higher ERI, higher overcommitment, and higher scores for four dimensions of the NWI-EO (organisation favouring communication between workers, support from the senior nurse, relationships between workers, support from the administration) than nursing aids. Nursing aids reported greater staffing inadequacy. Mean depression scores were higher for nursing aids (12.8 vs 10.9, p < 103).
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Variables associated with a higher CES-D score in bivariate analysis were: age 45 years, working during the daytime (only for the nursing aids subgroup), high ERI (with a doseeresponse relationship) and high overcommitment (Table 3). All the aggregated dimensions of the NWI-EO were significantly associated with the CES-D score for both registered nurses and nursing aids. Table 4 presents the regression coefficient estimates from the multilevel models explaining the CES-D score for the total sample. The null model indicates that there was a large level 1 variance for the general intercept between individuals, as could be expected for a health-related variable. Level 2 (work unit) and level 3 (hospital) variances represented 3.5% and 1.1% of the total variance respectively. After controlling for confounding factors, a high level of perceived ERI and a high level of overcommitment were associated with a significantly higher CES-D score (model 1). The interaction between ERI and overcommitment was globally significant (pvalue ¼ 0.03). In this model, total variance decreased by 21.9% compared with the null model, while level 2 and 3 variances decreased by 74.6% and 56.9%, respectively. Associations with CESD score were statistically significant for two of the five aggregated dimensions of the NWI-EO, after adjustment for confounding variables (model 2): low level of communication in the work unit, and bad relationships between workers within the work units. This model decreased the total variance by 3.6% compared with the null model. When the ERI variables and the NWI-EO were both included (model 3), regression coefficient estimates of the dimension “organisation favouring communication between workers” decreased by more than 100%, showing a mediating effect. Regression coefficient estimates of the dimension “relationships between workers within the work units” remained statistically significant in this third model. Results of stratified analysis by profession were similar. Table 5 presents the regression coefficient estimates from the multilevel models explaining the ERI score. The null model indicated that the relative distribution of the random intercept variance at three levels was about 84.7% variation at level 1 (individual), 11.0% variation at level 2 (work unit), and 4.3% variation at level 3
Table 2 Characteristics of the population.
Age (mean SE) (years)
Registered nurses n (%)
Nursing aids n (%)
p-value
35.8 9.2
40.5 9.4
<103
Speciality of work unit
Medicine Surgery Emergency or intensive care unit
633 (32.9) 581 (30.1) 713 (37.0)
543 (39.1) 450 (32.4) 396 (28.5)
<103
Working week
35 h/week < 35 h/week
1453 (75.4) 474 (24.6)
1100 (79.2) 289 (20.8)
0.010
Work schedule
Days only Alternate days/nights or nights only
811 (42.1) 1116 (57.9)
914 (65.8) 475 (34.2)
<103
Effortereward model (mean SE)
Effort score Reward score Effort/reward ratio Overcommitment score
18.6 18.5 0.73 15.7
4.4 4.9 0.22 3.6
16.9 18.3 0.66 14.8
4.4 5.1 0.21 3.7
<103 0.23 <103 <103
NWI-EO (mean SE)
1. 2. 3. 4. 5. 6. 7. 8.
7.6 6.8 8.7 5.9 11.3 6.7 11.7 7.5
2.4 3.4 3.7 2.4 2.9 3.0 3.1 3.4
6.6 6.5 9.5 5.0 10.2 6.6 11.0 7.4
2.3 3.2 3.7 2.6 3.0 3.2 3.4 3.3
<103 0.005 <103 <103 <103 0.32 <103 0.37 <103
Organisation favouring communication Support from the senior nurse Staffing adequacy to perform work Relationships between workers Interruptions during tasks Shared values Support from the administration Respect of planned days off and vacations
CES-D score (mean SE)
10.9 7.9
12.8 8.4
Total
1927 (100)
1389 (100)
SE: standard error.
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Table 3 CES-D score in relation to demographic, psychosocial and organisational variables by profession. Bivariate analysis using linear multilevel models and regression coefficients. Registered nurses Age (reference: <30 years) [30e44] 1.05* 45 years 2.83*** Speciality of work unit (reference: Emergency or ICU) Medicine 0.70y Surgery 0.25
Nursing aids 0.36 2.47*** 0.22 0.60
Working week (reference: part-time) Full-time
0.34
0.40
Schedule (reference: days only) Alternate days/nights or nights only
0.13
1.26*
Effort/reward ratio (reference: 1st quartile low) 2nd Quartile 3rd Quartile 4th Quartile (High)
1.47** 4.38*** 8.48***
1.55** 4.22*** 7.74***
Overcommitment (reference: Low) High
5.95***
6.39***
0.71***
0.63**
0.22** 0.20* 0.40** 0.27*
0.32* 0.22* 0.41** 0.36*
NWI-EO aggregated at level 2 Low level of communication in the work unit Lack of support from the senior nurse Staffing inadequacy to perform work Bad relationships between workers Non-respect of planned days off and vacations
Table 4 CES-D score in relation to psychosocial and organisational variables. Multivariate analysis using multilevel models (n ¼ 3316, 190 work units) and regression coefficients.
***p-value < 103, **0.01 < p < 103, *0.05 < p < 0.01, y0.20 < p < 0.05.
(hospital). In the model analysing the effect of the NWI-EO aggregated at level 2 on individual ERI perceptions (model 4), total variance decreased by 13.8% while level 2 and 3 variances decreased by 79.1% and 31.2%, respectively. After controlling for individual variables (model 5), the three variances were slightly modified. In this last model, three aggregated dimensions of the NWI-EO were significantly associated with higher ERI score: low level of communication in the work unit, staffing inadequacy and non-respect of planned days off and vacations. The first dimension accounted for the greatest decrease in level 2 variance.
Discussion The main finding of this cross-sectional analysis conducted among 3316 registered nurses and nursing aids working in French teaching hospitals was that some organisational constraints in the work unit, measured by the aggregated NWI-EO, were associated with individual depressive symptom scores, either as a direct effect or as a mediated effect through perceived ERI. Results suggested that poor relationships between workers in the work unit were associated with higher depressive symptom scores, regardless of ERI perception. Moreover, we found that low level of communication between workers within work units (concerning patients’ issues, psychological problems encountered by nurses, or organisation of work) was strongly associated with individual perceptions of ERI and indirectly associated with depressive symptoms. We also found that understaffing and the non-respect of planned days off and vacations were associated to a lesser extent with perceived ERI, but these organisational constraints were not associated with depressive symptoms. In addition, our results were concordant with the three hypotheses of the ERI model, as high perceived ERI and high level of overcommitment were related to depressive
Null Model
Model 1 Model 2 Model 3
Fixed effects ERI 1st Quartile (low) 2nd Quartile 3rd Quartile 4th Quartile (high)
0.00 1.15** 3.24*** 4.96***
0.00 1.26** 3.40*** 5.08***
Overcommitment Low High
0.00 4.06***
0.00 4.16***
0.00
0.00
0.49
0.57
0.46
0.56
1.46
1.44
Interaction overcommitment * ERI Low overcommitment and low ERI High overcommitment and medium low ERI High overcommitment and medium high ERI High overcommitment and high ERI NWI-EO (aggregated at level 2) Low level of communication in the work unit Lack of support from the senior nurse Staffing inadequacy to perform work Bad relationships between workers Non-respect of planned days off and vacations Random effects Level 1 (individuals) variance (SE) Level 2 (work unit) variance (SE) Level 3 (hospital) variance (SE) Total variance Relative variation of total variance compared with null model
0.42*
64.21 (1.63) 2.35 (0.65) 0.72 (0.56) 67.29
51.34 (1.30) 1.01 (0.42) 0.18 (0.20) 52.53 21.9%
0.10
0.05
0.03
0.04
0.16*
0.25*
0.26**
0.17
0.09
62.11 (1.57) 1.88 (0.59) 0.86 (0.64) 64.85 3.6%
51.18 (1.30) 1.01 (0.43) 0.24 (0.24) 52.44 22.0%
Model 1 ¼ ERI model (overcommitment þ ERI þ interaction overcommitment/ERI). Model 2 ¼ NWI-EO. Model 3 ¼ ERI model þ NWI-EO. All models were adjusted for age, profession, speciality of the work unit and work schedule. ***p-value < 103, **0.01 < p < 103, *0.05 < p < 0.01.
symptoms, and nurses reporting both high ERI and high level of overcommitment had a higher CES-D score. Limitations and strengths This study presents some limitations. The main limitation is due to the cross-sectional design. We cannot exclude reverse causation where respondents with depressive symptoms may over-report an unfavourable work environment. Some longitudinal studies have provided evidence for reciprocal causal relationships between the work characteristics (including ERI) and mental health, however these studies showed that causal effects were much higher than those for reversed causality (De Jonge et al., 2001; De Lange, Taris, Kompier, Houtman, & Bongers, 2004; Shimazu & de Jonge, 2009). Reverse causation seems all the more unlikely that we used results at the work group level. Another methodological limitation is related to common-method variance, as both the exposure and outcome variables are self-reported and based on individuals’ perceptions,
A. Jolivet et al. / Social Science & Medicine 71 (2010) 534e540 Table 5 ERI score in relation to organisational variables. Multivariate analysis using linear multilevel models and regression coefficients. Total sample (n ¼ 3316) Null Model Fixed effects NWI-EO Low level of communication in the work unit Lack of support from the senior nurse Staffing inadequacy to perform work Bad relationships between workers Non-respect of planned days off and vacations Random effects Level 1 (individuals) variance (SE) Level 2 (work unit) variance (SE) Level 3 (hospital) variance (SE) Total variance Relative variation of total variance compared with null model
Model 4
4.35*** 0.20 0.98*** 0.70** 0.52
411.505 (10.4) 53.59 (8.19) 20.64 (13.70) 485.28
393.11 (9.94) 11.19 (3.59) 14.18 (9.01) 418.48 13.8%
Model 5
3.30*** 0.27 1.38*** 0.31 0.59*
387.20 (9.80) 12.94 (3.80) 13.45 (8.74) 413.59 14.8%
Model 4:NWI-EO (unadjusted). Model 5:NWI-EO (adjusted for age, profession, speciality of the work unit, work week, work schedule). ***p-value < 103; **0.01 < p < 103; *0.05 < p < 0.01.
which can lead to inflated associations. However aggregating individual responses up to a work group level as been suggested as an alternative to limit this bias in organisational research (Kawachi, 2006). Another unlikely source of bias is a selection bias due to the elimination of 557 eligible subjects because of missing values or because they were in work units comprising less than two registered nurses and two nursing aids. Hospitals participated voluntarily and the study sample was female only. Therefore interpretation of the findings can only be made for women. Also, our findings cannot be generalised to other occupational groups in hospitals. The use of aggregated measures of the organisational work environment at the work unit level was limited to five dimensions of the NWI-EO because ICC(1,k) was lower than 0.60, which indicates heterogeneity of nurses’ perceptions within work units. Lastly, past medical history of depression, stressful life events and stressful factors in home life were not available in this study. These limitations are balanced by several strengths. Firstly, the participation rate was high. Secondly, we used random sampling of the work units. Thirdly, we used a multilevel model which takes into account the data hierarchies and the non-independence of observations within groups. Fourthly, we used aggregated data which allowed us to test a contextual effect of organisational factors on individual outcomes and to cancel out the impact of differences in personal perceptions. Finally, the “communication” and “relation” dimensions of the NWI-EO both benefit from a good concurrent validity: for registered nurses, NWI-EO scores for the communication possibilities dimension were significantly higher in work units where shift handovers were informal vs formal (following structured steps). For nursing aids, NWI-EO scores for relationships within the work unit were significantly higher when there were conflicts which disrupted organisation in the unit as assessed by the nurse manager interview.
Interpretation of the results Our findings with respect to the ERI model are in agreement with those of previous cross-sectional or longitudinal studies, showing that perception of effortereward imbalance influences
539
depressive disorders (Kivimaki et al., 2007; Siegrist et al., 2004; Stansfeld et al., 1999). However, associations between overcommitment and depressive symptoms on the one hand and between overcommitment/ERI interaction and depressive symptoms on the other hand are less consistent in the literature (Van Vegchel, 2005). Few nursing research studies have analysed the association between depression and organisational factors in hospitals. A cross-sectional study among 343 female employees from a large Danish hospital (patient care workers and laboratory technicians) showed that high levels of demand at work, low meaning of work and low social support at work (from colleagues and supervisors) were significantly associated with poorer mental health (Aust, Rugulies, Skakon, Scherzer, & Jensen, 2007). A cross-sectional survey carried out among the employees of two Spanish hospitals (n ¼ 313) showed that high psychological demands and low social support were associated with poor mental health (Escriba-Aguir & Tenias-Burillo, 2004). Lastly, a case-control study among 128 English healthcare professionals showed that employees presenting minor psychiatric disorders reported greater lack of management support and more role conflicts (Weinberg & Creed, 2000). There is abundant literature concerning intention to leave the profession, burnout and job satisfaction. A systematic review of published studies conducted to assess the association between organisational factors and burnout underlined the importance of support by supervisors, doctor/nurse relations, support by the administration and nurse staffing (Gershon et al., 2007). Moreover, studies which aimed to analyse the combined effect of both the ERI model and the Karasek model reported that perception of ERI and social support had an independent effect on health (Niedhammer et al., 2006; Stansfeld & Candy, 2006). Our analysis showed that poor team relations at the work unit level were associated with higher depressive scores regardless of ERI perception, but we found no relation with senior nurse support. We hypothesised that organisational factors within the work unit measured by the aggregated NWI-EO could have an impact on depressive symptoms through individual ERI perception. Our results suggest that organisational constraints in the work unit have a strong contextual effect on individual perceptions of ERI, as the differences between units in the level of ERI perceived by their nurses and nursing aids seem to be mainly explained by differences in the level of organisational constraints between these units. In the literature, we have found no epidemiological studies which suggested such mediation pathways between organisational constraints in the workplace and mental health through ERI perceptions. However, an intervention study supports our assumption. Bourbonnais, Brisson, Vinet, Vezina, and Lower (2006) developed a participative intervention among care providers in an acute care hospital in Quebec using a quasi-experimental design with a control group. Qualitative methods were used to identify adverse conditions, then specific solutions related to teamwork, team spirit, staffing processes, work organisation, training, communication, and ergonomy were implemented in the experimental group. After one year, results suggested that the intervention had a positive effect in the experimental group (Bourbonnais, Brisson, Vinet, Vezina, Abdous, et al., 2006) by reducing adverse psychosocial work factors, among them ERI which was considered as an intermediate effect, and by improving mental health outcomes, considered as the final effect of the intervention. Interventions mostly target individuals rather than work organisation by implementing stress management programmes, while many authors suggest that organisational approaches are more effective and have more important, longer-lasting effects than individual approaches (Kompier & Kristensen, 2000). Intervention studies based on the ERI model are limited and focused mainly on individual
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employees. Nevertheless, work environment improvement approaches according to this model have been proposed (Tsutsumi & Kawakami, 2004). They combine behavioural modifications but apply mainly socio-environmental and organisational strategies. Conclusion Our study and our theoretical model allowed us to identify and quantify organisational factors that are associated with mental health either directly or indirectly through perceived ERI. Such a mediating effect of organisational factors on health through ERI perceptions would provide one of the mechanisms through which interventions based on the ERI theory could be successful. Analysis of the prospective data of the ORSOSA study and the combination of multiple measurements of organisational factors, such as external assessments of organisational constraints in work units and individual data, will assist in drawing conclusions about causal relationships. References Aiken, L. H., & Patrician, P. A. (2000). Measuring organizational traits of hospitals: the revised nursing work index. Nursing Research, 49, 146e153. Aiken, M., & Hage, J. (1968). Organizational interdependence and intraorganizational structure. American Journal of Sociology, 33, 912e930. Aust, B., Rugulies, R., Skakon, J., Scherzer, T., & Jensen, C. (2007). Psychosocial work environment of hospital workers: validation of a comprehensive assessment scale. International Journal of Nursing Studies, 44, 814e825. Baron, R. M., & Kenny, D. A. (1986). The moderatoremediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173e1182. Bonde, J. P. (2008). Psychosocial factors at work and risk of depression: a systematic review of the epidemiological evidence. Occupational and Environmental Medicine, 65, 438e445. Bonneterre, V., Liaudy, S., Chatellier, G., Lang, T., & De Gaudemaris, R. (2008). Reliability, validity, and health issues arising from questionnaires used to measure Psychosocial and Organizational Work Factors (POWFs) among hospital nurses: a critical review. Journal of Nursing Measurement, 16, 207e230. Bourbonnais, R., Brisson, C., Vinet, A., Vezina, M., Abdous, B., & Gaudet, M. (2006). Effectiveness of a participative intervention on psychosocial work factors to prevent mental health problems in a hospital setting. Occupational and Environmental Medicine, 63, 335e342. Bourbonnais, R., Brisson, C., Vinet, A., Vezina, M., & Lower, A. (2006). Development and implementation of a participative intervention to improve the psychosocial work environment and mental health in an acute care hospital. Occupational and Environmental Medicine, 63, 326e334. De Jonge, J., Bosma, H., Peter, R., & Siegrist, J. (2000). Job strain, effortereward imbalance and employee well-being: a large-scale cross-sectional study. Social Science & Medicine, 50, 1317e1327. De Jonge, J., Dormann, C., Janssen, P. P. M., Dollard, M. F., Landeweerd, J. A., & Nijhuis, F. J. N. (2001). Testing reciprocal relationships between job characteristics and psychological well-being: a cross-lagged structural equation model. Journal of Occupational and Organizational Psychology, 74, 29e46. De Lange, A., Taris, T., Kompier, M., Houtman, I., & Bongers, P. (2004). The relationships between work characteristics and mental health: examining normal, reversed and reciprocal relationships in a 4-wave study. Work & Stress, 18, 149e166. Escriba-Aguir, V., & Tenias-Burillo, J. M. (2004). Psychological well-being among hospital personnel: the role of family demands and psychosocial work environment. International Archives of Occupational and Environmental Health, 77, 401e408. Fuhrer, R., & Rouillon, F. (1989). La version française de l’échelle CES-D: description et traduction de l’échelle d’auto-évaluation. Psychiatry and Psychobiology, 4, 163e166. Gershon, R. R., Stone, P. W., Zeltser, M., Faucett, J., MacDavitt, K., & Chou, S. S. (2007). Organizational climate and nurse health outcomes in the United States: a systematic review. Industrial Health, 45, 622e636.
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