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Ethical climate and intention to leave among critical care clinicians: an observational study in 68 intensive care units across Europe and the United States

  • Bo Van den BulckeEmail author
  • Victoria Metaxa
  • Anna K. Reyners
  • Katerina Rusinova
  • Hanne I. Jensen
  • J. Malmgren
  • Michael Darmon
  • Daniel Talmor
  • Anne-Pascale Meert
  • Laura Cancelliere
  • László Zubek
  • Paulo Maia
  • Andrej Michalsen
  • Erwin J. O. Kompanje
  • Peter Vlerick
  • Jolien Roels
  • Stijn Vansteelandt
  • Johan Decruyenaere
  • Elie Azoulay
  • Stijn Vanheule
  • Ruth Piers
  • Dominique Benoit
  • the DISPROPRICUS study group of the Ethics Section of the ESICM
Open Access
Original

Abstract

Purpose

Apart from organizational issues, quality of inter-professional collaboration during ethical decision-making may affect the intention to leave one’s job. To determine whether ethical climate is associated with the intention to leave after adjustment for country, ICU and clinicians characteristics.

Methods

Perceptions of the ethical climate among clinicians working in 68 adult ICUs in 12 European countries and the US were measured using a self-assessment questionnaire, together with job characteristics and intent to leave as a sub-analysis of the Dispropricus study. The validated ethical decision-making climate questionnaire included seven factors: not avoiding decision-making at end-of-life (EOL), mutual respect within the interdisciplinary team, open interdisciplinary reflection, ethical awareness, self-reflective physician leadership, active decision-making at end-of-life by physicians, and involvement of nurses in EOL. Hierarchical mixed effect models were used to assess associations between these factors, and the intent to leave in clinicians within ICUs, within the different countries.

Results

Of 3610 nurses and 1137 physicians providing ICU bedside care, 63.1% and 62.9% participated, respectively. Of 2992 participating clinicians, 782 (26.1%) had intent to leave, of which 27% nurses, 24% junior and 22.7% senior physicians. After adjustment for country, ICU and clinicians characteristics, mutual respect OR 0.77 (95% CI 0.66- 0.90), open interdisciplinary reflection (OR 0.73 [95% CI 0.62–0.86]) and not avoiding EOL decisions (OR 0.87 [95% CI 0.77–0.98]) were all associated with a lower intent to leave.

Conclusion

This is the first large multicenter study showing an independent association between clinicians’ intent to leave and the quality of the ethical climate in the ICU. Interventions to reduce intent to leave may be most effective when they focus on improving mutual respect, interdisciplinary reflection and active decision-making at EOL.

Keywords

Intent to leave Ethical climate Interdisciplinary reflection Decision-making Respect 

Take-home message

Interventions aiming to reduce or prevent intent to leave among the ICU workforce should focus on improving their ethical climate.

Introduction

It becomes more and more challenging for hospital managers worldwide to retain clinicians in intensive care units (ICU) [1, 2, 3, 4, 5]. Currently, about 18–23% of ICU clinicians express an intention to leave their job in the United States and Europe [6, 7]. Besides irregular working hours and night/weekend shifts in an often chaotic and noisy environment, clinicians are increasingly confronted with morally distressing situations often related to decision-making at end-of-life (EOL) [7, 8, 9, 10, 11, 12, 13]. The combination of technical innovation, which often prevents patient’s natural death, and the increasing number of potentially inappropriate admissions [7, 8, 14] render EOL decisions stressful, with postponed decision-making or even decision-paralysis as a consequence [7, 8, 14]. Whereas acute moral distress related to decision-paralysis may induce overt conflicts in the team [10, 15], more chronic forms of unexpressed moral distress such as frustration, guilt, maladaptive behavior, can ultimately cause job turnover [14, 15, 16, 17, 18, 19, 20, 21]. As one of the strongest and most important predictors of actual turnover in health care, besides job satisfaction, has been found to be turnover intention [1, 2, 3, 4, 5, 6]. Past efforts to reduce burnout and job leave have mainly focused on empowering individuals’ resilience skills [5, 7, 9]. However, timely sharing knowledge, experience and values between different professions within an open climate may further help in reducing moral distress and subsequently intention to leave [7, 8, 9, 10, 11, 12, 13, 14, 15, 20]. To our knowledge, the relationship between the intent to leave and the quality of inter-professional collaboration with regards to ethical decision-making in the ICU has never been assessed.

The main objective of this study, as shown in Fig. 1, was to assess the relationship between the quality of the ethical climate in the ICU and intent to leave after taking country, ICU, and clinician factors into account. We hypothesized that the better the quality of ethical climate in the ICU, the lower the intent to leave among clinicians.
Fig. 1

Theoretical framework. ICU mortality (2013) as a surrogate marker for cumulative confrontation with end-of-life

Methodology

Ethics

This study was approved by the ethics committees of all participating centers and the Danish National Health Authority. Informed consent was required in all countries. The questionnaires are available in the electronic supplementary material (ESM 1).

Data collection and ethical climate instruments

This study is part of the DISPROPRICUS study, which aimed to assess whether the quality of the ethical climate in ICU is associated with the predictive value of perceptions of excessive care, in regards to patients’ 1-year outcomes, as well as to the time until written treatment limitation decisions during ICU stay and death [14, 20].

ICU characteristics were collected by the local investigators between March and May 2014. Country-specific health variables were retrieved from a prior publication [14]. As proxy of the average wage at country level, we used countries’ Big Mac index (i.e. the cost of a Big Mac in 120 different countries) as retrieved from the world bank website. This index is a global, well-known and simple economic standard reflecting countries’ purchase power parity [21]. Clinicians of 68 adult ICUs in 12 European countries (Belgium, Czech Republic, Denmark, France, Germany, Greece, Hungary, Italy, Portugal, United Kingdom, Sweden, the Netherlands) and the US completed questionnaires on personal characteristics, working conditions and the ethical climate prevailing in their units using the ethical decision-making climate questionnaire (EDMCQ) [20]. This self-assessment questionnaire consists of 32 items with 4- or 5-point Likert scale options; 11 items are on end-of-life care practices [11]; 11 on interdisciplinary reflection, collaboration, and communication [22] and 11 on leadership skills of senior doctors [23, 24]. The theoretical framework of this instrument can be found in a previous publication [20]. The EDMCQ was first validated and determined via exploratory and confirmatory factor analysis, which identified seven important factors: F1 culture of not avoiding EOL decisions; F2 culture of mutual respect within the interdisciplinary team; F3 practice and culture of open interdisciplinary reflection; F4 self-reflective and empowering leadership by physician; F5 practice and culture of ethical awareness; F6 active decision-making by physicians; F7 active involvement of nurses in EOL care and decision-making [20]. Cluster analysis was subsequently used to determine categorically which kind of ethical decision climate characterized each of the ICUs [20, 25]. This analysis yielded four mutually exclusive climates: good, average with(+) and average without(−) involvement of nurses at end-of-life, and poor. The risk of death and of receiving a written treatment-limitation decision in patients perceived by clinicians as receiving excessive care was higher in ICUs with a good climate than in those with a poor one. The differences in these endpoints between the average and the poor climates were less obvious, but still in favor of the former compared to the latter, thus objectively validating the EDMCQ instrument [14, 20].

Next to the measured demographical characteristics, clinicians were also asked to report whether they actively considered leaving their current job [20, 14]. Although intention to leave is not always followed by action, the reverse relationship always exists, and intent can manifest itself some time before (from months to years) actually leaving the job [6]. For this reason, the intent to leave is presently regarded as “the most direct and immediate antecedent of overt turnover behavior” [26].

Data analysis

The primary endpoint of this study is intent to leave categorized as a binary (yes or no) outcome.

Univariate analysis

Fisher’s exact tests and Pearson Chi-square tests were used for comparing categorical variables and Mann–Whitney U tests (or t test where appropriate) for comparing continuous variables. Results are presented as numbers (%) and medians (25th–75th percentiles). Two-sided p values were calculated and compared with 5% to identify potential variables for inclusion in a subsequent multivariate analysis.

Multivariate analysis

We performed two hierarchical logistic mixed effect models to assess the multivariate associations between the characteristics reported in Table 1 and intention to leave, with independent random effects at the level of ICU and countries to account for correlation between measurements obtained in the same ICU, hospital and country [25]. The first model, including the four EDMCQ clusters, provides insight into the association between the overall quality of the ethical climate in a unit and intent to leave. The second model, including the seven EDMCQ factors, provides more detailed information on the association between each of the EDMCQ factors and clinicians’ intent to leave their job in a unit.
Table 1

Intent to leave: univariate analysis*

Variables

Overall

Intent to job leave

p value

Yes

No

Overall respondent

n = 2992

n = 782 (26.1%)

n = 2210 (73.9%)

 

Country level

 General economic factors (25th–75th percentile)

   Percentage of inhabitants > 65 year

18.0 (18.0–20.0)

18.0 (18.0–20.0)

18.0 (18.0–20.0)

0.823

  Number of ICU beds/100,000 inhabitants

6.7 (6.4–15.9)

6.7 (6.0–12.5)

6.7 (6.4–15.9)

0.016

    GDP** per inhabitant (dollar) (× 1000)

41.8 (30.8–48.1)

41.8 (30.8–51.8)

41.8 (30.7–48.1)

0.159

  GDP health expediture (%)

10.6 (9.7–11.7)

9.8 (9.7–11.3)

11.2 (9.7–12.9)

< 0.001

  GDP health expenditure per capita (x 1000)

5.1 (3.2–6.1)

5.1 (3.2–6.1)

5.1 (3.2–6.1)

0.498

  Big Mac index***

4.3 (4.0–4.8)

4.4 (4.0–4.9)

4.3 (4.0–4.8)

< 0.001

 Geographical region (%)

    Northern Europe

674 (22.5%)

228 (33.8%)

446 (66.7%)

< 0.001

    Western Europe/VS

1468 (49.1%)

337 (22.9%)

1131 (77.1%)

    Central Europe

513 (17.1%)

123 (23.9%)

390 (76.1%)

    Southern Europe

337 (11.3%)

94 (27.9%)

243 (72.1%)

Hospital level (%)

  Hospital type

    University

1787 (59.7%)

458 (25.6%)

1329 (74.4%)

0.671

  University affiliated

364 (12.2%)

104 (28.6%)

260 (71.4%)

  Hospital

749 (25.0%)

201 (26.8%)

548 (73.2%)

  Private

92 (3.1%)

19 (20.7%)

73 (79.3%)

  Total beds in hospital

    

  < 250

147 (4.9%)

40 (27.2%)

107 (72.8%)

< 0.001

    250–499

689 (23.0%)

207 (30.0%)

482 (70.0%)

    500–749

581 (19.4%)

168 (28.9%)

413 (71.1%)

  > 750

1575 (52.6%)

367 (23.3%)

1208 (76.7%)

ICU level (25th–75th percentile)

 General

    Number of beds per ICU

13.0 (9.0–22.0)

12.0 (9.0–16.0)

13.0 (9.0–24.0)

< 0.001

  Severity of illness

   ICU mortality in 2013 (in %)

13.0 (8.0–18.0)

14.0 (8.0–18.0)

13.0 (8.0–18.0)

< 0.001

   Length of stay in 2013 (in days)

4.0 (3.1–6.0)

4.6 (3.1–6.0)

4.0 (3.0–6.0)

0.057

 Organizational factors

    Staffing

   Patient to nurse ratio

1.7 (1.0–2.0)

1.5 (1.0–2.0)

2.0 (1.0–2.0)

0.311

   Patient to junior physician ratio

4.0 (2.0–6.0)

4.0 (2.0–5.8)

4.0 (2.0–6.0)

0.073

   Patient to senior physician ratio

6.0 (3.0–8.0)

6.0 (3.0–8.0)

7.0 (3.0–8.0)

0.109

   Part- of fulltime psychologist available

1760 (58.8%)

479 (61.3%)

1281 (57.9%)

0.118

      Physician salary (Euro x 1000) (15 years of working experience)

5.0 (3.2–7.3)

4.9 (3.2–6.3)

5.0 (3.2–7.3)

0.005

      Nurse salary (Euro x 1000) (15 years of working experience)

2.5 (1.9–2.8)

2.6 (1.9–2.9)

2.5 (1.9–2.8)

0.013

 Ethical decision-making climate (%)

    Good

535 (17.9%)

162 (30.3%)

373 (69.7%)

0.607

    Average with nurse involvement at EOL

1253 (41.9%)

332 (26.5%)

921 (73.5%)

    Average without nurse involvement at EOL

302 (10.1%)

65 (21.5%)

237 (78.5%)

    Poor

902 (30.1%)

223 (24.7%)

679 (75.3%)

Clinicians level (%)

  Age (25th–75th percentile)

38.0 (30.0–47.0)

37.0 (30.0–45.0)

39.0 (30.0–48.0)

0.002

  Male gender

858 (28.7%)

224 (26.1%)

634 (73.9%)

0.99

  Having a partner

2300 (76.9%)

561 (24.4%)

1739 (75.6%)

< 0.001

  Having children

1754 (58.6%)

431 (24.6%)

1323 (75.4%)

0.023

  Religion

  Non-religious

1190 (39.8%)

299 (25.1%)

891 (74.9%)

0.587

    Roman catholic

687 (22.9%)

184 (26.8%)

503 (73.2%)

    Protestant

534 (17.8%)

150 (28.1%)

384 (71.9%)

  Greek-orthodox

179 (5.9%)

36 (20.1%)

143 (79.9%)

  Muslim

30 (1.0%)

11 (36.6%)

19 (63.4%)

  Jewish

9 (0.3%)

4 (44.4%)

5 (65.6%)

    Budhist

10 (0.3%)

3 (33.3%)

7 (66.6%)

    Other

162 (5.4%)

51 (31.5%)

111 (68.5%)

    I do not wish to answer

191 (6.4%)

44 (5.6%)

147 (6.7%)

 Belief important to very important in attitude towards EOL

453 (15.1%)

132 (23.0%)

321 (77.0%)

0.128

 Role

  Nurses

2275 (76.0%)

615 (27.0%)

1660 (73.0%)

0.043

  Junior physicians

308 (10.3%)

74 (24.0%)

234 (76.0%)

  Senior physicians

409 (13.7%)

93 (22.7%)

316 (77.3%)

  Years of experience in the ICU (25th–75th percentile)

8.0 (3.0–16.0)

7.0 (3.0–13.8)

8.0 (3.0–18.0)

0.001

  Working conditions (25th–75th percentile)

  Hours working in a week

38.0 (32.0–40.0)

38.0 (35.0–40.0)

38.0 (32.0–40.0)

0.048

  Night shifts per month

5.0 (3.0–7.0)

5.0 (3.0–7.0)

5.0 (3.0–7.0)

0.256

  Day shifts during weekend per month

3.0 (2.0–4.0)

4.0 (2.0–5.0)

3.0 (2.0–4.0)

< 0.001

    Involved in research or ICU working group

1084 (36.2%)

285 (26.3%)

799 (73.7%)

0.919

  Ever been involved in medico-legal claim

258 (8.6%)

75 (29.1%)

183 (70.9%)

0.295

*Results are expressed by Chi square test as numbers (%) percentages out of the total number of participants (2992), and by Kruskal test as median (25th–75th percentile), **GDP: measure of a country’s economic output, gross domestics product; ***Big Mac index: the cost of a Big Mac in 120 different countries) as retrieved from the world bank website

The models were built using a backward elimination method. In particular, we started with a full model, including all characteristics that were identified as significantly associated with intent to leave at the 5% significance level in the univariate analysis and proceeded by removing characteristics with the highest p value, one by one recursively, until the p values for all characteristics were below 0.1. We checked for the presence of significant interaction effects. The sole interaction effect (p = 0.02) that was significant at the 5% level, namely between role and hours, was included in the final models. Results of the association between ethical climate clusters and factors were expressed in (adjusted) odds ratios (OR) together with 95% confidence intervals. To aid interpretation, the results from the fitted models were standardized to adjusted percentages for the entire population, using direct standardization [25]. In the standardization process, random effects were repeatedly drawn randomly from normal distributions centred at zero with variance given by its residual maximum likelihood estimate [27]. Approximate normal-based 95% confidence intervals for these adjusted percentages were calculated; in these, the sampling variance was obtained as the sampling variance of the standardized percentages upon ignoring the imprecision in the estimated regression coefficients, plus the variability in these percentages as the regression coefficients are repeatedly drawn from their (multivariate) sampling distributions centred at the maximum likelihood estimates. The analysis was performed in RStudio, version 1.0.15.

Since intention to leave is analyzed in a multi-level analysis approach, we also assessed which parts of the variance of intention to leave are on the country, ICU and the individual clinician level (Statistical Appendix).

Results

Country-, ICU- and clinician variables are reported in Table 1. Of 3610 nurses and 1137 physicians providing ICU bedside care, 2275 (63.1%) and 717 (62.9%), of which junior physicians 308 (61.5%) and 409 (63%) senior physicians working in 68 ICUs participated, respectively.

Respectively, 17.9%, 41.9%, 10.1% and 30.1% of clinicians worked in an ICU with a good, average(+), average(−) and poor climate. Overall, 782 clinicians (26.14%) had the intention to leave their job, of which 615 (27.0%) were nurses, 74 (24.0%) junior physicians, and 93 (22.7%) senior physicians.

Differences between clinicians with and without intent to leave are provided in Table 1. After adjusting for clinicians’ characteristics within an ICU and country, the risk of intent to leave was lower in clinicians working in ICUs in a good (OR 0.58, 95% CI 0.35–0.96), average(+) (OR 0.68, 95% CI 0.46–0.99) and average(−) (OR 0.62, 95% CI 0.40–0.98) climate compared to clinicians working in ICUs with a poor climate. Results are provided in Table 2. The adjusted probabilities to leave one’s job in the respective climates are shown in Fig. 2 (all p < 0.05 in comparison to the poor climate). The most important independent ethical climate factors associated with intent to leave were mutual respect within the interdisciplinary team (OR 0.77 95% CI 0.66–0.90), open interdisciplinary reflection (OR 0.73 95% CI 0.62–0.86) and not avoiding EOL decisions by physicians (OR 0.87 95% CI 0.77–0.98) (Table 2). Interestingly, younger age, clinicians working in countries with a higher Big Mac index and clinicians working in ICUs with a higher mortality, were independent factors, significantly associated with a higher intent to job leave in both models (with a p < 0.05). Figure 3 shows a significant interaction effect between professional role and average hours per week of clinicians as associated with intent to leave. Clinicians who worked more hours per week had a higher intent to leave, especially if they were in a nursing role (p = 0.004).
Table 2

Multivariate analyses on intent to leave (adjusted odds ratio [95% confidence interval])

 

Model including EDMCQ clusters

Model including EDMCQ factors

Country

 Big mac index

1.65 [1.05,2.60]b

1.86 [1.14,2.88]b

  Healthcare expenditure per capita (divided by 100)

NS

NS

  Percentage over 65 years

NS

NS

Hospital

 Number of beds

NS

NS

ICU

 Patient to nurse ratio

NS

0.76 [0.61,0.95]b

  Patient to junior physician ratio

NS

NS

  Psychologist available

NS

NS

  Total number of beds ICU

NS

NS

 ICU mortality in 2013

1.03 [1.003,1.05]b

1.03 [1.005,1.05]b

Ethical climate

  Good

0.58 [0.35,0.96]b

  Average+

0.68(0.46–0.99)b

  Average

0.62 [0.40,0.98]b

  Poor

1

Factors EDM climate

  Not avoiding EOL decisions

0.87 [0.77,0.98]b

  Mutual respect

0.77 [0.66,0.90]c

  Open interdisciplinary reflection

0.73 [0.62,0.86]d

  Self-reflective leadership

NS

  Ethical awareness

NS

  Active decision making

0.87 [0.75,1.006]a

  Active involvement of nurses

NS

Clinician

  Medicolegal claim

NS

NS

  Age

0.98 [0.97,0.99]d

0.98 [0.97,0.99]d

  Gender

NS

NS

  Hours worked per week

NS

NS

Belief

 (Very) important

NS

NS

  Not religious

NS

NS

  Not (very) important

NS

NS

Professional role

  Nurse

0.27 [0.09,0.82]b

0.18 [0.06,0.55]b

  Junior doctor

0.27 [0.06,1.12]a

0.22 [0.05,1.01]a

  Senior doctor (Ref)

1

1

Interaction between professional role and hours worked per week*

  Nurse

1.03 [1.01–1.06]b

1.03 [1.01–1.06]c

  Junior doctor

1.02 [0.99–1.05]a

NS

  Senior doctor (Ref)

1

1

  Intercept of model

0.12 [0.01,1.11]a

0.11 [0.01,1.21]a

Data used of resp. 2992. Results of the association between ethical climate clusters and factors were expressed in (adjusted) odds ratios (OR) together with 95% confidence intervals

*Interaction effect between professional role and hours worked per week as shown in Fig. 3

ap < 0.10

bp < 0.05

cp < 0.01

dp < 0.001

Fig. 2

Adjusted probabilities to leave one’s job in the respective climates (all p < 0.05 in comparison to the poor climate). Adjusted risk of intent to job leave, expressing the percentage of health care professionals who would have intentions to leave their job if they all worked in a good, average+, average or poor ethical climate, respectively, along with 95% confidence intervals. (Poor: 0.3442 [0.3402,0.3481], average+: 0.2686 [0.26510,0.2720], average: 0.2537 [0.2503,0.2570], good: 0.24 [0.2389,0.2455])

Fig. 3

Hours worked per week and professional role as intent to leave predictors. It shows how the role of the clinician interacts with the number of hours working per week. It shows predictions of the model (with interaction term) on population level (not accounting for random effect variances, i.e. a ‘typical’ ICU, hospital and country) of the probability for intent to job leave in function of the number of hours working per week and the role of the clinician. The intervals shown are confidence intervals for the predicted values

Discussion

This is the first large multicenter study showing that the quality of the ethical climate in ICU is associated with the intention to leave one’s job, even after accounting for the impact of country, ICU and clinician characteristics. Measuring ethical climate by means of the EDMCQ [20] helped to identify several modifiable factors, which could be targeted to reduce intent to leave in the ICU.

Moreover, our study reveals that job mobility is more substantial in countries with a higher purchasing power [2, 6, 21, 28], and confirms that younger ICU clinicians tend to be less afraid to leave their current workplace [28, 29]. These results suggest that less modifiable external/environmental factors (e.g., labor market, perceived employment opportunities, job alternatives, economic concerns,…) and clinician characteristics (e.g. age) might play an important role in ICU clinicians’ intention or willingness to enter, leave or remain in the current job, profession and/or the organization as well [16, 29, 30].

Although pay and financial benefits may substantially help in reducing the intent to leave an ICU job [6, 28, 30], creating favorable working conditions for clinicians by ensuring a right work–family balance and lowering the work pressure [1, 2, 28, 30] may be at least as important. Limiting the number of working hours per week is one of the measures to achieve this goal and has already been identified as an important factor in several previous studies [2, 5, 6, 30]. We found that this was specifically more important in nurses (Fig. 3).

Extending previous research on the detrimental effect of high mortality in the ICU on workload, moral distress and burnout [7, 8, 11, 31], our study highlights its positive association with intent to leave. This suggests that intent to leave could be further reduced by improving triage and advanced care planning before ICU admission [32]. Moreover, our study showed a protective association between the quality of the ethical climate and intent to leave in the ICU which is in line with contemporary studies where lack of collaboration, disrespectful communication and distrust among team members are recognized as direct factors of increased job dissatisfaction and moral distress among ICU clinicians [7, 19, 33, 34, 35, 36].

Moral distress occurs when an individual’s moral integrity is seriously compromised, either because one feels unable to act in accordance with core values or obligations, or attempted actions fail to achieve the desired outcome [37]. Therefore, moving from pure knowledge-based discussions to more knowledge and value-based reflections may be of utmost importance to reduce clinicians’ moral distress [14, 15, 20] and quality of care [7, 8, 14, 32]. Mutual respect which allows interdisciplinary reflection [33, 36, 39], together with the non-avoidance of EOL decisions in the ICU, were the two most important ethical climate factors associated with a lower intent to leave the job in our study. The key position of senior physicians in the EDM process [7, 8, 12, 14] and the fact that senior doctors tend to overrate their leadership- and decision-making capacities at EOL [11, 12] naturally points them for future interventions, especially in ICUs with a poor ethical climate [14]. Restoring meaning and a sense of wellbeing in physicians may not only improve intention to leave but might also make the ICU a highly respected and desirable place to work [7, 8, 12, 15, 37]. Every clinician needs to feel confident to promote change within the team for the benefit of the patient and their families [15, 32, 36, 37, 38, 39]. To develop the practice of mutual respect within a team, senior physicians should act as role models [14, 20, 36, 37, 38, 39]. This includes giving respectful feedback, empowering staff to voice perceptions and emotions, facilitating an ethical climate, where difficult decisions are not postponed but made in a timely fashion following open discussions [7, 8, 12, 14, 20, 36]. Our EDMCQ scale is a valuable addition and update to existing ethical climate scales focusing on physicians and nurses, as well as different factors within ICU units, e.g. unit physician leadership, which all have profound effects on the ethical climate [12, 14, 15, 20].

Strengths of the study include the large number and multi-national inclusion of participants, the use of a validated questionnaire to assess the ethical climate in the ICU, the high response rate of 63% and the use of logistic mixed effect models to account for correlation within ICUs and countries, as well as standardization to aid interpretation. Our study also has some limitations. First, the ICUs were not selected at random, which may have affected the external validity of our results. Second, all variables were measured with self-reported questions, so a common method bias may exist [40]. To increase the validity of the outcomes, assessment of actual turnover behavior ought to be included in future research. Within our cross-sectional approach, we could not enable causal interpretations [25, 27]. Future studies should longitudinally examine how ethical climate in the ICU and its outcomes develop over time, or evaluate the effect of specific interventions on the ethical climate. Finally, we did not explore meanings associated with ethical decision-making and the intent to leave, using qualitative research (e.g. focus groups). Nevertheless, the EDMCQ instrument enables ICUs to take a ‘snapshot’ of the EDM, as perceived by their team members. The findings of our study suggest that multidimensional interventions are necessary to address ethical climates at ICU- and individual level. Further research should focus on interview perceptions of staff members within their ICUs to create tailored and sustainable interventions to improve mutual respect, interdisciplinary reflections and active decision-making at end of life.

Conclusion

This is the first large multicenter study showing an independent association between clinicians’ intention to leave their job and the quality of the ethical climate in ICU. Interventions aiming to reduce or prevent intent to leave among the ICU workforce, may be more effective when they focus on improving their ethical climate through encouraging mutual respect, open interdisciplinary reflection and active decision-making by making (senior) physicians aware of their unique position in facilitating discussions about EOL decisions.

Notes

Acknowledgements

This study was supported by a European Society of Intensive Care Medicine/European Critical Care Research Network clinical research award and a Fonds voor Wetenschappelijk Onderzoek senior clinical investigators grant (1800513N) obtained in 2012 by DB. We are grateful to all the ICUs and clinicians who participated in our study and to Jolien Roels for having performed the multivariate analysis (under supervision of DB and SVS). Likewise, we would like to thank all the national coordinators (please see affiliations below).

Participating centers and local investigators

Belgium: University Hospital, Vrije Universiteit Brussel, Brussels (Herbert Spapen, Marie-Claire Van Malderen, Godelieve Opdenacker), Leuven University Hospital, Leuven (Geert Meyfroidt, Dieter Mesotten, Joost Wauters, Marie Van Laer and Alexander Wilmer, Joost Wauters, Helga Ceunen), ZNA Stuivenberg, Antwerpen (Inneke E De Laet, Anita Jans), Ghent University Hospital, Gent (Dominique Benoit, Sandra Oeyen, Ingrid Herck, Stephanie Bracke, Charlotte Clauwaert), Institut Jules Bordet, Bruxelles (Meert Anne-Pascale, Leclercq Nathalie), CHU-Brugmann, Bruxelles (Devriendt Jacques), CHU Saint Pierre, Bruxelles (Dechamps Philippe), Czech Republic: Liberec District Hospital, Liberec (Ivana Zykova), Masaryk University, Brno and University Hospital, Brno (Jan Malaska), Third Faculty of Medicine, Charles University, Prague (Matous Schmidt), Hospital and Polyclinic Havirov, Havirov (Igor Satinsky), Institute for Experimental and Clinical Medicine, Prague (Eva Kieslichova), 3rd Medical Department, First Faculty of Medicine, Charles University in Prague and General University Hospital, Prague (Jarmila Krizova), Karlovy Vary District Hospital, Karlovy Vary (Robert Janda), Pardubice District Hospital, Pardubice (Magdalena Fortova, Jiri Matyas), First Faculty of Medicine, Charles University and General University Hospital, Prague (Katerina Rusinova, Ondrej Kopecky), Denmark: Herning Hospital, Herning (Christian Alves Køhler Pedersen), Kolding Hospital, Kolding (Stine Hebsgaard), Vejle Hospital, Vejle (Rikke Frank Aagaard Johnsen), Holbæk Hospital, Holbæk (Tina Charlotte Bitsch Hansen), France: Saint-Etienne University Hospital and Jacques Lisfranc Medical School, Saint-Etienne (Michael Darmon), Saint-Louis University Hospital, APHP, Université Paris-7, Paris (Danielle Reuter, Elie Azoulay), Institut Paoli Calmette, Marseilles (Djamel Mokart), Montfermeil Hospital, Montfermeil (François Vincent), Germany: University Hospital Jena, Jena (Christiane S. Hartog), Viersen General Hospital, Viersen (Peter Gretenkort), Tettnang Hospital, Tettnang (Andrej Michalsen), Greece: Agia Olga Hospital, Athens (Aikaterini Kounougeri), Evangelismos Hospital, Athens (Serafim Nanas), Agios Pavlos Hospital, Thessaloniki (Despina Papachristou), AHEPA University Hospital, Thessaloniki, (Ioanna Soultati), G.Gennimatas Hospital, Thessaloniki (Dimitrios Lathyris), Hippokratio General Hospital, Thessaloniki (Marili Pasakiotou), Papageorgiou General Hospital, Thessaloniki (Marina Oikonomou), Hungary: Semmelweis University Budapest, Budapest (Gábor Élő, Orsolya Szűcs), Kaposi Mór Teaching Hospital, Kaposvár University, Kaposvár (János Fogas), St. Stephen and St. Leslie Metropolitan Hospital, Budapest (Ilona Bobek), Italy: Azienda Ospedaliero Universitaria, “Maggiore della Carità”, Novara, and Department of Translational Medicine, Università del Piemonte Orientale, Novara (Francesco Della Corte, Carlo Olivieri, Rosanna Vaschetto, Laura Cancelliere), Ospedale Civile San Salvatore, and Department of Life, Health and Environmental Sciences (MeSVA), University of L’Aquila and Department of Emergency, San Salvatore Hospital, L’Aquila (Franco Marinangeli, Tullio Pozone, Alessandra Ciccozzi), The Netherlands: Canisius Wilhelmina Ziekenhuis, Nijmegen (A. Schouten, Monique Bruns), Medical Center Leeuwarden, Leeuwarden (Rik T. Gerritsen, Matty Koopmans), Erasmus University Hospital of Rotterdam (Erwin Kompanje, Ditty van Duijn), University of Groningen and University Medical Center Groningen, Groningen (Jan G. Zijlstra, Anne KL Reyners), Wilhelmina Ziekenhuis Assen, Assen (Johan G. Lutisan), Portugal: Hospital S.António, Porto (Raquel Monte, José António Pinho, Pedro Pimenta), CHVNG, Vila Nova de Gaia (Paula Fernandes, Ana Isabel Paixão), Instituto Português de Oncologia, Porto (Filomena Faria), Sweden: Sahlgrenska University Hospital, Gothenburg (Johan A. Malmgren), Sahlgrenska University Hospital/Östra, Gothenburg (Bertil Andersson), Skåne University Hospital, Malmö (Eva Åkerman), Karolinska University Hospital, Karolinska (Andreas Hvarfner), The Hospital of Norrköping, Norrköping (Robert Svensson), United Kingdom: King’s College Hospital, London (Victoria Metaxa), USA: Beth Israel Deaconess Medical Center and Harvard Medical School, Boston MA (Daniel Talmor, Ariel Mueller, Valerie Banner-Goodspeed), Henry Mayo Newhall Memorial Hospital, Valencia, CA (Dee Rickett), Mayo Clinic, Rochester, MN (Michael E. Wilson, Richard Hinds).

Author contributions

All authors had their substantial contributions to the conception or design of the work, or the acquisition, analysis or interpretation of data, drafting the work or revising it critically for important intellectual content and their final approval of the version published. Every author gave his/her agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Study concept and design: BB, DB, RP. Design of the questionnaire: DB, HIJ, JM, SV, EJOK, JD, BB, EA, RP. Coordination of the translation of the questionnaire: HIJ, JM, VM, AKR, MD, KR, DT, AM, LC, LZ, PM, AM. Acquisition of data: BB, HIJ, JM, VM, AKR, MD, KR, DT, AM, LC, LZ, PM, AM, Gadeyne. Analysis and interpretation of data: BB, DB, SV, JR, SV, RP. Drafting of the manuscript: BB, DB, VM, SV, BB, SV, PV, RP. Critical revision of the manuscript for important intellectual content: BB, DB, HIJ, JM, VM, AKR, MD, KR, DT, AM, LC, LZ, PM, AM, SV, EJOK, JD, JR, SV, JR, EA, RP. Statistical expertise: JR, SV. Obtained funding: DB, JD. Administrative, technical, or material support: DB, JD. Steering committee: DB, SV, EJOK, JD, SV, Gadeyne, BB, EA, RP.

Funding

This study was supported by a ESCIM/ECCRN clinical research award and a FWO senior clinical investigators Grant (1800513N) obtained in 2012, and prolonged in 2017 by DDB.

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflict of interests.

Supplementary material

134_2019_5829_MOESM1_ESM.docx (50 kb)
Supplementary material 1 (DOCX 49 kb)
134_2019_5829_MOESM2_ESM.docx (17 kb)
Supplementary material 2 (DOCX 17 kb)

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Copyright information

© The Author(s) 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Bo Van den Bulcke
    • 1
    Email author
  • Victoria Metaxa
    • 2
  • Anna K. Reyners
    • 3
  • Katerina Rusinova
    • 4
  • Hanne I. Jensen
    • 5
  • J. Malmgren
    • 6
    • 7
  • Michael Darmon
    • 8
  • Daniel Talmor
    • 9
  • Anne-Pascale Meert
    • 10
  • Laura Cancelliere
    • 11
  • László Zubek
    • 12
  • Paulo Maia
    • 13
  • Andrej Michalsen
    • 14
  • Erwin J. O. Kompanje
    • 15
  • Peter Vlerick
    • 16
  • Jolien Roels
    • 17
  • Stijn Vansteelandt
    • 17
    • 18
  • Johan Decruyenaere
    • 1
  • Elie Azoulay
    • 8
  • Stijn Vanheule
    • 19
  • Ruth Piers
    • 20
  • Dominique Benoit
    • 1
  • the DISPROPRICUS study group of the Ethics Section of the ESICM
  1. 1.Department of Intensive Care MedicineGhent University HospitalGhentBelgium
  2. 2.King’s College HospitalLondonUK
  3. 3.Department of Medical Oncology, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
  4. 4.Department of Anesthesiology and Intensive Care, First Faculty of MedicineCharles University in Prague and General University Hospital in PraguePragueCzech Republic
  5. 5.Department of Intensive Care Medicine, Institute of Regional ResearchVejle HospitalVejleDenmark
  6. 6.Department of Anaesthesiology and Intensive CareSahlgrenska University HospitalGothenburgSweden
  7. 7.University of Southern DenmarkOdenseDenmark
  8. 8.Hôpital Saint-Louis and University Paris-7ParisFrance
  9. 9.Department of Anesthesia, Critical Care, and Pain MedicineBeth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUSA
  10. 10.Service des Medicine Interne, Soins Intensifs et Urgences OncologiquesInstitut Jules Bordet, ULBBrusselsBelgium
  11. 11.SCDU Anestesia e Rianimazione, Azienda and Ospedaliero UniversitariaMaggiore della CaritàNovaraItaly
  12. 12.Semmelweis University BudapestBudapestHungary
  13. 13.Intensive Care DepartmentHospital S.AntónioPortoPortugal
  14. 14.Tettnang HospitalTettnangGermany
  15. 15.Department of Intensive Care MedicineErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
  16. 16.Faculty of Psychology and Educational Sciences, Department of Personnel Management, Work and Organizational PsychologyGhent UniversityGhentBelgium
  17. 17.Department of Applied Mathematics, Computer Science and Statistics, Faculty of SciencesGhent UniversityGhentBelgium
  18. 18.London School of Hygiene and Tropical MedicineLondonUK
  19. 19.Department of Psycho-analysis and Clinical Consulting, Faculty of Psychology and Educational SciencesGhent UniversityGhentBelgium
  20. 20.Department of Geriatric MedicineGhent University HospitalGhentBelgium

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