DOI: https://doi.org/10.4414/smw.2019.20033
Intensive care units (ICUs) are challenging work environments, in which complex dependencies exist between teamwork and clinician burnout [1–3]. Perceived clinician burnout and teamwork quality can vary depending on demographic or unit characteristics, including workload. The purpose of this study was to identify risk factors in Swiss ICUs that explain clinician burnout and negative teamwork experiences.
Teamwork is central to healthcare delivery. However, working effectively as a team continues to constitute a challenge in critical care [4–6]. For instance, nurses have more negative attitudes towards teamwork than physicians [7]. These discrepant attitudes are attributed to hierarchical differences in which those with lower status may find it more difficult to speak up or feel that their input is not well received, which can adversely affect patient safety [8–10]. Furthermore, challenging working conditions in ICUs are associated with decreased wellbeing: for instance, extensive workload is associated with higher burnout [11, 12].
However, effects of demographic and unit characteristics seem to be specific to the setting, as they differ considerably between studies. Healthcare delivery in ICUs varies across countries depending on factors such as available resources, cultural and best practice norms [13–17]. Thus, the findings of existing studies may not be transferable.
An international study investigating working conditions of nurses in low-acuity wards showed that Swiss nurses report lower burnout compared with nurses in other countries [18]. However, clinicians working in clinical areas with critically ill patients, such as ICUs, are generally at higher risk for burnout and its consequences – it is unlikely that Switzerland is an exception [11, 19].
Moreover, little is known about the impact of demographic characteristics on perceptions of teamwork and clinician burnout in Swiss ICUs. Lastly, objective workload and unit characteristics are rarely considered [20]. For instance, one study found that males (compared to females) and nurse assistants (compared to nurses and physicians) reported higher burnout; however, the role of unit characteristics was unclear [13].
The primary aim of this study was to explore the role of demographic characteristics related to the clinical context such as professional experience in explaining clinicians’ experiences of teamwork and burnout. Based on previous studies investigating other work settings, we assume that clinicians in the early stages of their career (trainee status and low professional experience), and those working full time and predominantly nightshifts will experience higher burnout, as they are likely to perceive their work environment as more demanding [21–24]. Drawing from previous studies set in other healthcare contexts, we assume that clinicians in the later stages of their career (high professional experience and leadership positions), physicians and those that are part of the core team (i.e., working day shifts and full time) will report higher quality of teamwork [7, 25, 26].
The secondary aim of this study was to investigate the association of unit characteristics and workload with clinicians’ perceptions of teamwork and clinician burnout. ICUs are based in different hospital types (e.g., university or regional), vary in size, and specialise in different subdisciplines to address the needs of different patient populations. Due to these different patient populations, specific facets of workload, such as the amount of nursing interventions, are also likely to vary between ICUs [27, 28]. Based on the job demands-resources model, which states that physical, social and emotional workload can deplete employees’ energy and results in decreased wellbeing, we propose that clinicians with higher workload will report lower quality of teamwork and higher burnout [21, 29]. We also explored the role of unit size, type of hospital and ICU specialisation. The results of this study help to identify potentially harmful ICU working conditions and occupational groups and that are at risk for experiencing low-quality teamwork and increased burnout, thus contributing to informed decisions on work design or preventative interventions.
This cross-sectional study combined survey data from clinicians (including nurses and physicians) working in Swiss ICUs with unit characteristics that were extracted from the MDSi database (“minimaler Datensatz der SGI-SSMI” [Schweizerische Gesellschaft für Intensivmedizin] – “minimal dataset of SGI-SSMI” [Swiss Society of Intensive Medicine]) which accumulates patient and unit data routinely collected by Swiss ICUs.
Consent to participate from clinicians and approval to use the MDSi data were acquired in three steps. First, we signed an agreement of collaboration with the steering committee of the SGI-SSMI in 2013. The SGI-SSMI initiated contact between the study team and the ICUs and provided us with the MDSi data of participating units for the duration of the study period. ICU nursing and medical leaders that chose to participate signed a consent form, thus agreeing to inclusion of the ICU’s MDSi data. For confidentiality reasons, ICU leaders were responsible for forwarding an online questionnaire consisting of demographic questions and measures of teamwork and burnout to the staff in our name. Survey participants were assured complete anonymity and confidential handling of their data upon accessing the questionnaire and gave their consent to participate before they could proceed to the survey questions.
Unit characteristics and workload data were drawn from the MDSi database. To prevent identification of individual patients, after consultation with a medical consultant responsible for the MDSi database, unit means (nursing interventions) or sums (number of shifts with agitated patients/ventilation) were calculated from individual patient data by the company responsible for administration of MDSi data prior to data export.
Ethics approval was granted by the University of Fribourg (75, 2013-06-03) and, where required by cantonal legislation, cantonal ethics committees (Bern: Z044/13; Fribourg: 024/13-CER-FR; Zurich: 28/13). Data collection of the survey and from the MDSi database took place for one month on each unit in September and October 2013.
We collected data on professional role (nurse, physician), professional status (trainee/non-trainee and leadership/non-leadership role), level of employment (full-time/part-time), predominant shift (day/night), and professional experience and tenure in the ICU (all in years) via the online survey. Trainees were defined as nurses training to become an intensive care certified nurse and physicians training to become intensive care, anaesthesiology, surgery, emergency or internal medicine specialists. Leadership roles were defined as being the medical or nursing leader of the ICU.
We collected data on hospital type (university, cantonal/regional) and unit specialization (surgical/medical, paediatric, interdisciplinary) through the online survey.
Data on unit size (number of beds in use) were exported from the MDSi database.
We extracted three indicators from the MDSi that capture different aspects of workload: patient agitation, patient ventilation, and nursing interventions [30–32].
Patient agitation was assessed with the Sedation Agitation Scale (SAS) on a 7-point Likert scale (1 = unarousable, 7 = dangerous agitation) [33, 34]. Of note, the Richmond Agitation-Sedation Scale (RASS) is used in some units, with transformation to SAS during export in the central database [35]. In each shift, each patient is given a SAS score. We calculated the percentage of shifts with agitated patients by considering the total number of shifts across all patients in which a patient scored 4 (agitated) or higher on the SAS and divided it by the total number of shifts worked during the data collection period.
Patient ventilation. According to MDSi guidelines, patients are categorised as ventilated if they are mechanically ventilated at least 2 hours in a three-shift system or 3 hours in a two-shift system [36]. We calculated the percentage of shifts with ventilated patients by considering the total number of shifts across all patients in which a patient was categorised as ventilated, and divided it by the total number of shifts worked during the data collection period.
Nursing interventions were calculated based on the Nine Equivalents of Nursing Manpower Scale (NEMS) [31, 37, 38]. This instrument was designed to measure nursing workload in ICUs. A patient can be assigned a score between 0 and 56 on each shift based on nine different nursing care interventions (such as application of intravenous medication) that are weighted based on effort [31]. We considered the mean number of NEMS interventions per unit and multiplied it by the number of patients who had stayed in the unit during the data collection period to calculate the total workload. We then divided this figure by the number of full-time nursing equivalents (FTE; taken from the MDSi) of nurses with ICU specialization to adjust the total workload by the available nursing staff.
All scales had previously been translated from English and validated in German, French, and Italian [39–47]. Besides theoretical considerations such as covering different aspects of teamwork and availability in three languages, the scales were chosen because they have been explicitly worded for or tested in the healthcare context, as not all aspects of teamwork (such as team innovation) are of significance in this context. We conducted a pilot study by asking 37 nurses and physicians in all three language regions to provide written feedback on questionnaire wording to ensure that the questionnaire had been correctly translated from English and German into French and Italian as spoken in Switzerland, that the correct terms for different professional roles etc. had been used in all languages, and that the questionnaire items were applicable to the healthcare context. The feedback showed that the items were applicable to the healthcare context and worded appropriately. Some slight alterations regarding correct vocabulary and technical terms (for professional roles) were made after consultation with native speakers of the respective languages and ICU experts. In addition, we improved our rationale for collecting demographic data. The individual scores for all teamwork and burnout scales were generated by calculating the sum of all items and dividing it by the number of items.
We used three scales measuring cognitive, behavioural, and interpersonal aspects of teamwork. The nine-item safety organising scale assesses a teams’ organising and coordination efforts, as well as underlying cognitions such as the extent to which team members share a cognitive representation on work processes [39, 40, 48]. A sample item is “We have a good map of each other’s talents and skills”. Responses were given on a 7-point Likert scale (1 = not at all, 7 = to a very great extent). The possible sum score on this scale ranges from 9 to 63.
The three-item nurse-physician-relations scale from the nursing work index revised (NWI-R) measures the quality of interprofessional teamwork (sample item: “Physicians and nurses have good working relationships”) [41–43]. Responses were given on a 4-point Likert scale (1 = disagree, 4 = agree), which results in a sum score ranging from 3 to 12.
Finally, we measured psychological safety, which is defined as the shared belief that the team is safe for interpersonal risk-taking [49, 50]. A sample item of this seven-item scale is “Members of this team are able to bring up problems and tough issues”. Responses were given on a 5-point Likert scale (1 = very inaccurate, 5 = very accurate). The sum score of this scale ranges between 5 and 35.
Burnout was assessed with the Maslach Burnout Inventory-Human Services (MBI-HSS), which is the standard instrument to assess burnout and has been validated in a variety of contexts and languages [44–47]. The MBI-HSS consists of the three dimensions emotional exhaustion – characterized by mental and physical fatigue (nine items, sample item “I feel mentally exhausted because of my work”), depersonalisation, which describes cognitive and emotional disengagement from one’s job (five items, sample item “I doubt the significance of my work”), and personal accomplishment – the perception of achieving something worthwhile at one’s job (seven items, reverse scored, sample item “I deal very effectively with the problems at my work”). Responses were given on a 7-point Likert scale (0 = never, 6 = always). The sum scores of this scale range from nine to 63 (emotional exhaustion), five to 35 (depersonalisation), and seven to 49 (personal accomplishment), respectively.
In addition to standardised measures, we invited participants to provide additional information they thought might be relevant in relation to teamwork and clinician burnout.
We generated descriptive statistics of all measures, Pearson correlation coefficients between continuous variables and Cronbach’s alpha reliability coefficients for the teamwork and burnout scales using SPSS version 24 (table S1 in appendix 1). Unit-level means of teamwork and burnout scales were calculated from individual scores and then correlated with unit-level variables to avoid over-inflation of correlation coefficients by assigning the same value of a unit-level variables to all individuals of that unit (table S2).
Participants were grouped into high, moderate or low categories of burnout on each of the three burnout dimensions based on the scoring scheme by Maslach et al. [46]
To investigate associations of teamwork and burnout with predictor variables, we conducted multilevel regression analyses using Mplus version 7 [51]. Dichotomous variables were dummy-coded. Categorical variables were dichotomised, dummy-coded and tested against a reference category according to standard guidelines (see table 2) [52].
Prior to the main analyses, we explored the data distribution of categorical data. Apart from the dichotomous and categorical variables, we found that personal accomplishment (skewness = −0.69, standard error [SE] = 0.06); kurtosis: 3.59, SE = 0.13) and nursing interventions (skewness = 1.89, SE = 0.30); kurtosis: 3.38, SE = .60) did not meet the criteria for normal univariate distribution (skew and kurtosis between −2 and +2) [53].
For this reason, we used the maximum likelihood parameter estimator (MLM) with standard errors that are robust to non-normality of data for estimating the model parameters. [51, 54].
Lastly, we thematically grouped participants’ replies to the open-ended question by the two major topics teamwork and clinician burnout to illustrate the results of the statistical analyses.
Out of 82 ICUs, 60 agreed to participate, which constitutes a participation rate of 73%. We excluded five ICUs from the analyses because of missing MDSi data or low response rate within the unit (n <3) to allow for sufficient variety within teams following recommendations of previous studies, resulting in a final sample of 55 ICUs and 1496 nurses and physicians [55].
Descriptive statistics of the ICUs and clinicians are summarised in tables 1 and 2 , respectively. Cronbach’s alpha values for teamwork and burnout measures ranged from 0.60 to 0.91, indicating acceptable to excellent internal reliability (table S1 in appendix 1). Raw Pearson correlation coefficients are reported in the online supplement (table S1 for individual level and table S2 for unit level variables). The results of the multilevel regression analyses are provided in table 2. Standardised regression coefficients are reported to account for the different scaling of predictor variables (see table 1). The coefficients indicate the change in the dependent variables that corresponds to the change of one standard deviation of the predictor variable [51].
Table 1 Descriptive statistics of intensive care units (n = 55).
| Frequency | Per cent | ||||
|---|---|---|---|---|---|
| Type of hospital | University | 7 | 12.7 | ||
| Cantonal/Regional | 48 | 87.3 | |||
| Type of ICU | Medical/Surgical | 12 | 21.8 | ||
| Paediatric | 2 | 3.6 | |||
| Interdisciplinary | 41 | 74.5 | |||
| Mean | Standard deviation | Median | Range | ||
| Unit size (number of beds in use) | 14.0 | 5.4 | 8.0 | 6.0–34.1 | |
| Number of patients during survey period | 81.7 | 50.1 | 73.0 | 20.0–309.0 | |
| Number of nursing shifts during survey period | 685.9 | 448.3 | 542.0 | 190.0–2324.0 | |
| Full time equivalents* | 26.4 | 24.4 | 18.4 | 3.3–144.4 | |
| Workload | Nursing interventions† (number) | 727.9 | 357.3 | 620.1 | 219.1–1974.8 |
| Patient agitation‡ (%) | 10.5 | 10.5 | 7.3 | 0.0–55.0 | |
| Ventilation days§ (%) | 30.6 | 18.7 | 31.4 | 0.0–78.0 | |
Note: All data except type of hospital were taken from the MDSi. * Equivalent of nurses working full-time † Number of nursing interventions as recorded via the NEMS (nine equivalents of nursing manpower) scale × total number of shifts / FTE [31, 37, 38]. ‡ Percentage of shifts during survey period with patients scoring > 4 on the SAS (sedation agitation scale) [35, 36]. § Percentage of shifts during survey period with mechanical ventilation. Please refer to the methods section for a detailed description of the variables.
Table 2 Descriptive statistics of survey participants (n = 1496).
| Frequency | Per cent | ||||
|---|---|---|---|---|---|
| Language* | German | 1121 | 74.9 | ||
| French | 247 | 16.5 | |||
| Italian | 128 | 8.6 | |||
| Gender* | Male | 366 | 24.5 | ||
| Female | 1041 | 69.6 | |||
| Professional role* | Nurse | 1148 | 76.7 | ||
| Physician | 243 | 16.2 | |||
| Head RNs | 123 | 5.2 | |||
| Intensive care RNs | 793 | 52.9 | |||
| RNs in intensive care training | 117 | 7.8 | |||
| Head physicians | 83 | 4.7 | |||
| Senior physicians | 85 | 5.7 | |||
| Resident physicians | 77 | 5.1 | |||
| Level of employment* | Full time | 725 | 48.5 | ||
| Part time | 695 | 46.5 | |||
| Predominant shift* | Day | 1013 | 67.7 | ||
| Night | 407 | 27.2 | |||
| Mean | Standard deviation | Median | Range | ||
| Age (years) | 39.6 | 9.4 | 39.0 | 19.0–63.0 | |
| Professional experience (years) | 12.6 | 8.9 | 11.0 | 0.0–43.0 | |
| Tenure (years in ICU) | 8.2 | 7.7 | 6.0 | 0.0–37.0 | |
| Teamwork | Safety organising | 5.2 | 0.8 | 5.3 | 1.0–7.0 |
| Psychological safety | 3.7 | 0.6 | 3.7 | 1.0–4.0 | |
| Interprofessional teamwork | 3.1 | 0.6 | 3.0 | 1.1–5.0 | |
| Burnout | Emotional exhaustion | 2.7 | 0.8 | 2.7 | 1.0–5.6 |
| Depersonalisation | 2.3 | 0.8 | 2.2 | 1.0–5.0 | |
| Personal accomplishment | 4.8 | 0.5 | 4.9 | 1.0–6.0 | |
All variables were taken from the survey. RN = registered nurse. Safety organising, interprofessional collaboration and psychological safety are subdimensions of teamwork. Emotional exhaustion, depersonalisation, and personal accomplishment are subdimensions of burnout. Please refer to the methods section for a detailed description of the variables. * Missing from 100%: participants did not provide this information
Physicians (compared with nurses), clinicians in leadership positions, and clinicians working predominantly day shifts reported higher quality of teamwork dimensions. Clinicians with longer ICU tenure reported better safety organising and trainees reported lower interprofessional teamwork (table 2).
Clinicians reported lower safety organising in ICUs with a higher proportion of shifts with mechanical ventilation and in university hospitals. Clinicians also reported higher psychological safety in larger ICUs.
Of the 1496 study participants, 11.8% scored high on all burnout dimensions. Of these, 37.8% reported high emotional exhaustion, 35.8% high depersonalisation, and 6.8% reported low personal accomplishment. Compared with normative scores of the MBI, participants of the current study scored higher on emotional exhaustion and depersonalisation, and lower on personal accomplishment [46]. Details on participants’ burnout scores are presented in table 3.
Table 3 Number and percentage of participants reporting high, moderate, and low levels of the respective burnout dimensions (n = 1496).
| High | Moderate | Low | ||||
|---|---|---|---|---|---|---|
| Frequency | Per cent | Frequency | Per cent | Frequency | Per cent | |
| Emotional exhaustion | 567 | 37.8 | 722 | 48.1 | 212 | 9.3 |
| Depersonalisation | 537 | 35.8 | 825 | 55.0 | 139 | 9.3 |
| Personal accomplishment | 408 | 27.2 | 991 | 66.0 | 102 | 6.8 |
Clinicians working predominantly night shifts reported higher burnout. Furthermore, trainees reported higher emotional exhaustion, those with low professional experience reported higher depersonalisation, and clinicians in leadership positions reported higher personal accomplishment (see table 2).
Analyses of teamwork (safety organising, psychological safety, interprofessional teamwork,) and burnout (emotional exhaustion, depersonalisation, personal accomplishment) on demographic and unit characteristics are summarised in table 4 . Clinicians working on ICUs with more mechanical ventilation or agitated patients reported higher emotional exhaustion. More nursing interventions predicted higher depersonalization and lower personal accomplishment scores. Perception of personal accomplishment was also significantly lower in university hospitals (compared to cantonal/regional hospitals). Clinicians working in paediatric ICUs (compared to interdisciplinary ICUs) reported lower emotional exhaustion and depersonalization; whereas clinicians working in surgical/medial ICUs (compared to interdisciplinary ICUs) reported h higher emotional exhaustion.
Table 4 Results of multilevel regression analyses of teamwork (safety organising, psychological safety, interprofessional teamwork) and burnout (emotional exhaustion, depersonalisation, personal accomplishment) on demographic and unit characteristics.
| Safety organising | Psychological safet | Interprofessional teamwork | Emotional exhaustion | Depersonalisation | Personal accomplishment | |
|---|---|---|---|---|---|---|
| Estimate (SE) | Estimate (SE) | Estimate (SE) | Estimate (SE) | Estimate (SE) | Estimate (SE) | |
| Individual level predictors | ||||||
| Professional role† | 0.17*** (0.04) | 0.18** (0.06) | 0.26*** (0.04) | 0.01 (0.04) | 0.04 (0.03) | 0.02 (0.04) |
| Professional experience (years) | −0.08 (0.06) | −0.01 (0.06) | −0.06 (0.05) | 0.08 (0.04) | −0.10** (0.04) | 0.01 (0.04) |
| Tenure (years in ICU) | 0.10* (0.05) | 0.04 (0.04) | 0.05 (0.04) | −0.06 (0.04) | 0.01 (0.04) | 0.07 (0.04) |
| Trainee status‡ | 0.02 (0.03) | −0.02 (0.03) | −0.06* (0.03) | 0.10** (0.04) | 0.05 (0.04) | −0.03 (0.04) |
| Leadership role§ | 0.07** (0.02) | 0.07** (0.03) | 0.12*** (0.03) | −0.03 (0.03) | −0.03 (0.02) | 0.07** (0.03) |
| Level of employment¶ | 0.04 (0.03) | 0.01 (0.03) | 0.04 (0.03) | −0.02 (0.03) | 0.03 (0.03) | −0.04 (0.03) |
| Predominant shift‖ | −0.10*** (0.03) | −0.09** (0.03) | −0.05* (0.02) | 0.09** (0.03) | 0.09** (0.0) | −0.10** (0.03) |
| R 2 | 0.06** (0.02) | 0.05* (0.02) | 0.10*** (0.02) | 0.02** (0.01) | 0.03* (0.01) | 0.03** (0.01) |
| Unit level predictors | ||||||
| Type of hospital¶¶: university | −0.54* (0.25) | −0.21 (0.16) | −0.24 (0.21) | 0.21 (0.15) | 0.11 (0.13) | −0.48** (0.14) |
| Type of ICU‖‖: medical/surgical | 0.13 (0.20) | 0.07 (0.17) | 0.12 (0.15) | 0.43*** (0.10) | −0.09 (0.11) | −0.14 (0.14) |
| Type of ICU‖‖: paediatric | 0.00 (0.03) | −0.03 (0.03) | −0.03 (0.04) | −0.38*** (0.12) | −0.27*** (0.05) | 0.04 (0.05) |
| Unit size (number of beds in use) | 0.33 (0.03) | 0.31* (0.16) | 0.12 (0.19) | −0.61** (0.20) | −0.07 (0.16) | 0.36* (0.19) |
| Workload: | ||||||
| Nursing interventions†† | −0.05 (0.05) | 0.10 (0.13) | −0.06 (0.14) | −0.18 (0.12) | 0.31* (0.12) | −0.38** (0.14) |
| Patient agitation‡‡ | −0.07 (0.07) | −0.19 (0.17) | 0.05 (0.12) | 0.58** (0.20) | −0.01 (0.13) | −0.08 (0.16) |
| Ventilation§§ | −0.27* (0.25) | −0.17 (0.14) | −0.04 (0.16) | 0.65*** (0.16) | 0.28 (0.18) | −0.41 (0.25) |
| R 2 | 0.25** (0.13) | 0.15* (0.05) | 0.06 (0.06) | 0.93*** (0.28) | 0.27* (0.14) | 0.54* (0.26) |
n (individual level) = 1496; n (unit level) = 55. Standardised regression coefficients are reported. * p <0.05 (two-tailed test); ** p <0.01 (two-tailed test); *** p <0.001 (two-tailed test). SE = standard error. R2 indicates the variance explained in each model. † Professional role: 0 = nurse, 1 = physician. ‡ Trainee status: 0 = not in training, 1 = in training. § Leadership role: 0 = no leadership role, 1 = leadership role. ¶ Level of employment: 0 = part-time, 1 = full-time. ‖ Predominant shift: 0 = day, 1 = night. †† Nursing interventions as recorded via the NEMS (nine equivalents of nursing manpower) scale × total number of shifts / FTE (full-time equivalents) [31, 37, 38]. ‡‡ Percentage of shifts during survey period with patients scoring >4 on the SAS (sedation agitation scale) [35, 36]. §§ Percentage of shifts during survey period with mechanical ventilation. ¶¶ Compared with regional and cantonal hospitals. ‖‖ Compared with interdisciplinary ICUs. Please refer to the methods section for a detailed description of the variables.
The selected quotes in table S3 (appendix 1) of the online supplement point out challenges regarding effective teamwork and communication across professional and hierarchical boundaries and levels of experience. They also highlight stressors besides quantitative workload, such as agitated and complex patients and competitive work cultures. Finally, the preventive effects of work environments characterized by good interprofessional collaboration and positive team climate became apparent.
The present study shows that workload on ICUs is associated with clinician burnout, and, to a lesser extent, with reduced perceptions of safety organizing. One third of clinicians reported high levels of at least one burnout dimension. The study expands the knowledge of demographic characteristics in the Swiss intensive care context.
The consistent pattern of demographic characteristics associated with certain perceptions of teamwork is in line with previous studies on discrepant attitudes toward teamwork depending on professional role and seniority. They may stem from the different cultures in which nurses and physicians are educated. Moreover, clinicians in higher levels of the healthcare hierarchy might be less affected by difficulties to speak up or to resolve conflict [7].
With regard to burnout, results indicate that the various occupational groups represented in this study may face different challenges: clinicians in training may be overwhelmed by the combination of the intensive care work environment and the demands of their training, and thus be at high risk for emotional exhaustion. Clinicians in leadership positions reported the highest levels of personal accomplishment, thus suggesting that as they progress through their careers they develop a sense of achievement – symptoms of burnout were not as prevalent [56].
Clinicians working predominantly night shifts stood out as a group in this study. During night shifts, fewer clinicians are available, thus increasing the responsibility and potentially workload of the demographic which might put them at risk for burnout and make effective teamwork – particularly communication with other members of the ward team – more difficult [57, 58]. According to previous studies, while working the night shift can but does not necessarily pose a health risk when well-managed, working over the regular shift length does [59–61].
In the present study, instead of subjective perceptions, we used workload surrogates extracted from the MDSi. Results indicated that both emotionally (e.g., caring for a large proportion of agitated or ventilated patients) and quantitatively (e.g., more nursing interventions per FTE) demanding work environments carry a risk for increased burnout.
Finally, the occupational environment may play a role in shaping clinicians’ perception of teamwork and burnout. University hospitals treat complex patients with higher mortality [62, 63]. This might explain why clinicians working in university hospitals reported lower safety organizing and personal accomplishment. Moreover, the balance of workload and resources associated with burnout may differ between ICU specialties [21].
The cross-sectional analyses we conducted do not allow for assumptions concerning causal relationships. Not all ICUs in Switzerland participated in this study, hence, there may be a selection bias as some ICUs indicated during the recruitment phase that they felt unable to participate due to their high workload. If these ICUs had participated, associations between study variables might have been even more pronounced.
Previous studies yielded mixed results regarding the accuracy of organizational indicators such as NEMS or FTE’s that were exported from the MDSi [38, 64, 65]. For instance, the ratio of registered nurses with ICU certification and registered nurses with no ICU certification may differ between units, resulting in a different skill mix and rendering some calculations using FTE’s less reliable. For this reason, we chose to calculate the percentage of shifts with ventilation and agitated patients as surrogates of workload instead of adjusting these figures using FTE’s, as we consider the overall accuracy of NEMS scoring, documentation of mechanical ventilation and patients’ agitation to be within clinically acceptable range [64]. Moreover, figures such as NEMS are also used by Swiss insurance companies for reimbursement, and this should guide the clinician to strive for valid documentation.
As teamwork and burnout are self-report measures, they represent individual’s perceptions and could be biased by momentary emotional states etc. Abstract constructs cannot be measured with the same level of external accuracy as physical attributes. The advantage of self-report measures is to gain insight into otherwise non-observable states and attitudes. Ultimately, inner psychological states and cognitions are related to externally observable behaviours [66–68].
The magnitude of effect sizes shows that the predictors analyzed in this study are not the only variables in this context that are associated with perceptions of teamwork and burnout. This is to be expected, as other contextual variables have been extensively studied [69–71].
The results of the current study can inform practitioners that are aiming to improve teamwork and reduce burnout in ICUs of specific target areas. The differences between ICU and hospital type indicate that factors potentially affecting teamwork and burnout vary considerably depending on the work environment. Hence, there is no ‘one size fits all’ solution to improve teamwork and reduce burnout. Instead, some work environments may be particularly challenging and thus should be prioritized. In addition, the study identifies occupational groups potentially at risk for burnout.
Depending on differences in professional role or status or predominant shift, clinicians in this study did not experience teamwork in the same way, even though they are exposed to the same teamwork environment. Shared interactions and experiences between team members – may they be subtle and interpersonal or explicit and task-related – shape individual cognitions, emotions and motivation as well as team interpersonal and task-related behaviors. If certain groups of clinicians have the impression that their input is not valued or that different opinions exist on how to accomplish a certain task, it can impact team effectiveness and affect wellbeing [10, 72]. Thus, it is important for a team to include all members in interprofessional communication, and understand that besides medical skills and knowledge, team processes contribute significantly to performance.
We found that burnout levels in Swiss ICUs were much higher as compared to clinicians working in other medical specialties [18, 73]. Clinicians who are not a member of the core team may be particularly at risk for burnout. High workload may not just a subjectively perceived problem, but also an organizational concern and should be managed accordingly to avoid the negative consequences of burnout such as sick leave, reduced patient safety and associated financial costs [1, 74, 75].
This study contributes to explaining variance of teamwork and burnout in Swiss ICUs.
Based on levels of reported teamwork and burnout, university hospitals and surgical/medical ICUs may be particularly challenging work environments. Even though they are exposed to the same environment, members of different professional groups and statuses have different perceptions of teamwork quality, which may manifest in team behavior. Special attention should be paid to clinicians working night shifts. Fourth, high, objectively measured workload is associated with burnout and as such should be actively managed.
Table S1 Individual-level Pearson correlations between demographic characteristics, and teamwork (safety organising, psychological safety, interprofessional teamwork) and burnout (emotional exhaustion, depersonalisation, personal accomplishment).
| Cronbach’s alpha | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Professional rolea | |||||||||||||
| 2 | Trainee statusb | 0.32** | ||||||||||||
| 3 | Leadership rolec | 0.21** | –0.06* | |||||||||||
| 4 | Level of employmentd | 0.10** | 0.22** | –0.01 | ||||||||||
| 5 | Predominant shifte | –0.11** | –0.05 | –0.20** | –0.09** | |||||||||
| 6 | Professional experience (years) | –0.23** | –0.28** | 0.09** | –0.29** | 0.07* | ||||||||
| 7 | Tenure (years in ICU) | –0.16** | –0.31** | 0.16** | –0.23** | 0.06* | 0.75** | |||||||
| 8 | Safety organising | 0.91 | 0.18** | 0.06* | 0.11** | 0.04 | –0.13** | 0.00 | –0.03 | |||||
| 9 | Psychological safety | 0.86 | 0.19** | 0.01 | 0.10** | –0.03 | –0.09** | –0.02 | –0.03 | 0.60** | ||||
| 10 | Interprofessional teamwork | 0.83 | 0.24** | 0.03 | 0.16** | 0.04 | –0.11** | –0.02 | –0.04 | 0.48** | 0.47** | |||
| 11 | Emotional exhaustion | 0.87 | 0.00 | 0.10** | –0.05 | 0.01 | 0.08** | –0.01 | 0.01 | –0.26** | –0.30** | –0.23** | ||
| 12 | Depersonalisation | 0.63 | 0.03 | 0.08** | –0.08** | 0.06* | 0.04 | –0.10** | –0.13** | –0.22** | –0.18** | –0.18** | 0.50** | |
| 13 | Personal accomplishment | 0.60 | 0.02 | –0.04 | 0.11** | –0.04 | –0.08** | 0.10** | 0.10** | 0.30** | 0.25** | 0.24** | –0.35** | –0.43** |
n = 1496. * p <0.05 (two-tailed test); ** p <0.01 (two-tailed test); *** p <0.001 (two-tailed test) a Professional role: 0 = nurse, 1=physician. b Trainee status: 0 = not in training, 1 = in training (includes nurses and physicians in training). c Leadership role: 0 = no leadership role, 1 = leadership role (includes nurses and physicians in leadership roles). d Level of employment: 0 = part-time, 1 = full-time. e Predominant shift: 0 = day, 1 = night. All variables were taken from the survey. Please refer to the methods section for a detailed description of the variables.
Table S2 Unit-level Pearson correlations between unit characteristics, and teamwork (safety organising, psychological safety, interprofessional teamwork) and burnout (emotional exhaustion, depersonalisation, personal accomplishment).
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Unit size (number of beds) |
|||||||||
| 2 | Nursing interventionsa | –0.27* | ||||||||
| 3 | Patient agitationb | 0.72** | –0.23* | |||||||
| 4 | Ventilationc | 0.62** | –0.14 | 0.47** | ||||||
| 5 | Safety organising | –0.26* | 0.00 | –0.27* | –0.27* | |||||
| 6 | Psychological safety | 0.06 | 0.09 | –0.08 | –0.10 | 0.69** | ||||
| 7 | Interprofessional teamwork | –0.21 | 0.00 | –0.15 | –0.14 | 0.56** | 0.41** | |||
| 8 | Emotional exhaustion | 0.18 | –0.16 | 0.32** | 0.32** | –0.49** | –0.47** | –0.30* | ||
| 9 | Depersonalisation | 0.06 | 0.27* | 0.03 | 0.17 | –0.44** | –0.24* | –0.27* | 0.47** | |
| 10 | Personal accomplishment | –0.17 | –0.07 | –0.12 | –0.20 | 0.23* | 0.05 | 0.04 | –0.19 | –0.52** |
n = 55. * p <0.05 (one-tailed test); **p <0.01 (one-tailed test); ***p <0.001 (one-tailed test) a Nursing interventions as recorded via the NEMS scale * total number of shifts / FTE [31, 37, 38]. b Percentage of shifts during survey period with patients scoring >4 on the SAS scale [35, 36]. c Percentage of shifts during survey period with mechanical ventilation. Variables unit size, nursing interventions, patient agitation and ventilation were extracted from the MDSi. All other variables were taken from the survey. Please refer to the methods section for a detailed description of the variables.
Table S3 Selection of participants’ responses to open-ended questions, grouped by topic.
| Teamwork | Challenges to interprofessional collaboration / hierarchy | Positive aspects and improvements | ||||
|---|---|---|---|---|---|---|
| The residents…have … inconsistent skills, but more discretion and sometimes less clinical insight [than nurses]- which makes it more difficult for me, when a resident exceeds his / her competence without consulting me. (Anaesthetist, 46) | I have the chance to work in an intensive care unit in which the working atmosphere is excellent both in the collaboration between caregivers and between doctors of all levels and caregivers. I think that this atmosphere brings a lot to the quality of our work when it comes to the care of patients. (Registered ICU nurse, 36) | |||||
| There is a gap in the relations between the top and the bottom, which has consequences on the interprofessional relations (doctors-nurses) but also on the hierarchical level (leadership position or not). (Resident physician, 35) | Since [date], we have two doctors with Intensive Care training. One feels that the doctors take on responsibility for the patients as for us, we have clearer conversations. Cooperation is increasing. (ICU head nurse, 41) | |||||
| Residents who … are beginners sometimes complicate our collaboration. (Registered ICU nurse, 43) | Because of the team climate it is still possible for me to work in this great profession after nine years. (Registered ICU nurse, 49) | |||||
| Daily contact with the [nursing] management, the offices are side by side, thus short distances. (Lead anaesthetist, 50) | ||||||
| Strain / burnout | General comments | Personnel availability | Work environment | Teamwork | Shift work | Positive aspects / improvement |
| I have been working 100% in my profession for 26 years and at the moment I feel exhausted after only a few days after my vacation…it worries me. (Registered ICU nurse, 44) |
Personnel availability is the key to … avoid overburdening employees. (ICU trainee nurse, 29) | In the last few years, things have changed. The patients are multimorbid, older, more confused, … the noise level (alarms) is much higher. It is not possible to finish a task, and this promotes stress and dissatisfaction but also irritability. (Registered ICU nurse, 43) |
I feel that within the intensive care teams ... there is always a kind of competition, a need to mark the territory, to acquire the trust of others and to prove oneself. This environment stresses me. (Registered nurse, 26) |
I think night work is considerably more tiring than the other shifts. (Registered ICU nurse, 46) | It would be helpful to have someone in charge of supporting the staff psychologically, who can act promptly, and set up training that provides the possibility to use tools / strategies to improve team work and safety. I would set up group meetings on a monthly basis to get a sense of the motivation, the team climate and discuss any problematic situations. (Registered nurse, 36) |
|
| I have the impression that I will not reach pension age alive, sane & calm if I keep working like this. (Resident, 35) | At the safety level, I think the patients are safe but not the staff. We are often confronted with verbal and physical violence. (Registered ICU nurse, 44) | One of the most severe burdens in our profession is the nightshift. (Paediatrician, 50) | With the help of private supervision, I have been able to grow through the processing of many unpleasant experiences, to gain new strength and confidence. (Registered ICU nurse, 36) | |||
| Delirious / confused patients are more stressful, and their number is increasing. (Registered ICU nurse, 30) |
||||||
This table is intended for illustrative purposes. We did not formally analyse the responses to open-ended questions. Quotes were translated to English from French, German and Italian.
We would like to thank the Swiss Society for Intensive Care Medicine (SGI-SSMI), all study participants and the local study coordinators for their collaboration throughout this project. We would also like to thank Corinna Galliano and Mina Askovic for their help with translating participants’ quotes into English.
This study was funded by the Swiss National Science Foundation (grant numbers PP00P1_128616 and P2FRP1_168482).
No potential conflicts of interest relevant to this article were reported.
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This study was funded by the Swiss National Science Foundation (grant numbers PP00P1_128616 and P2FRP1_168482).
No potential conflicts of interest relevant to this article were reported.