You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


See related commentary by Jubran, <http://ccforum.com/content/16/1/115>

Introduction
============

Optimal management of mechanical ventilation and weaning requires dynamic and collaborative decision making to minimize complications and avoid delays in the transition to extubation. Effective collaboration requires open, extensive, and coordinated communication as well as shared team goals and will result in improved quality of care, patient safety and discharge outcomes \[[@B1]-[@B3]\]. In the absence of collaboration, ventilation decision making may be fragmented, inconsistent, and delayed \[[@B4]\].

Previous studies exploring interprofessional responsibility for ventilation and weaning decision making in Australia, New Zealand, and Denmark found that physicians and nurses actively collaborated in the management of ventilation and weaning, generally in the absence of protocols \[[@B5]-[@B8]\]. Nurses in Australia and New Zealand were frequently independently responsible for manipulation of ventilator settings titrated to physiologic parameters \[[@B9]\]. Intensive care unit (ICU) organizational characteristics have been noted as key contributors to ICU performance and patient outcomes \[[@B10]\]. Organizational characteristics such as staffing ratios, hierarchical structure, and ICU team functioning in the above countries may differ from those elsewhere \[[@B11]\].

International variation in aspects of the delivery of mechanical ventilation such as preferred ventilator mode, use of non-invasive ventilation (NIV), and adoption of protocols for weaning has been noted previously \[[@B12],[@B13]\]. Interprofessional roles and responsibilities are influenced by differences in unit structure, staffing and skill-mix, patient case-mix, and medical and nursing leadership models \[[@B14]\]. The primary objective of our study was to describe the professional group with responsibility for determining key ventilation and weaning decisions including: selection of initial ventilator settings, titration of ventilator settings, weaning readiness, weaning method, extubation readiness, and weaning failure. We hypothesized that substantial variation would exist between and within countries for the professional group responsible for these decisions.

Our secondary objectives were to examine organizational characteristics associated with nurse involvement in ventilator and weaning decision making including nurse-to-patient ratios for invasive and non-invasive ventilation; perceived nursing autonomy and nursing contribution to ventilator decision-making; to describe the use of automated systems, protocols and/or guidelines for the management of mechanical ventilation and weaning; and the availability of education related to mechanical ventilation and associated processes for nurses. Results from the Netherlands have been previously reported in abstract form \[[@B15]\].

Materials and methods
=====================

Study Design and Sampling Frame
-------------------------------

We conducted a multi-center, cross sectional, self-administered survey of adult ICUs in Denmark, Germany, Greece, Italy, Norway, Switzerland, the Netherlands and the United Kingdom (UK). These countries represent three of the four European sub-regions: Northern, Western, and Southern Europe. Our sample frame comprised all ICUs providing mechanical ventilation to critically ill adults in Denmark, Norway, Switzerland, the UK, and the Netherlands identified through existing intensive care networks. For example, ICUs in the UK were identified using the 2008 Directory of Critical Care \[[@B16]\]. Telephone contact was made to confirm that the ICU met inclusion criteria and to obtain nurse manager contact details. In Germany, Greece, and Italy we were unable to identify a reliable comprehensive list of all adult ICUs. Therefore nurse managers were recruited from existing personal e-mail lists within regions of a country (Attica in Greece and the Piedmont and Valle D\'Aosta Regions in Italy) and nationally via advertisements in local journals and websites.

Study Population
----------------

We included nurse managers of adult ICUs providing care to ventilated patients. We requested nurse managers consult senior medical colleagues and other senior nurses involved in the clinical management of ventilated patients to provide the best possible reflection of ventilation and weaning processes within their unit. If more than one nurse manager was employed in an ICU, we requested that only one survey be returned that reflected a consensus of opinion. Pediatric and neonatal ICUs or units not routinely providing mechanical ventilation such as coronary care and high dependency units were excluded.

Survey Development and Testing
------------------------------

We administered a survey of mechanical ventilation and weaning responsibilities previously described and conducted in Australia and New Zealand \[[@B5]\]. Due to increased commercial availability of automated closed loop systems \[[@B17],[@B18]\], we added a question on the use of SmartCare/PS™ (Dräger Medical, Lübeck, Germany), Adaptive Support Ventilation (ASV) (Hamilton Medical, Bonaduz, Switzerland), Proportional Assist Ventilation (PAV), and Mandatory Minute Ventilation (MMV). Questions relating to ICU demographic and staffing descriptions were contextually adapted for each country based on input from senior nurses and physicians. The survey (see Additional file [1](#S1){ref-type="supplementary-material"}) was then forward and back translated into the required languages. Country coordinators (fluent in English and the native language) and the principal investigator resolved inconsistencies in the two English versions (initial version and back-translated). Once the two English versions were consistent, the translated version was revised and checked by another native speaker. Prior to distribution, face validity was assessed in each country by a panel of experienced ICU nurses and physicians.

Data Collection
---------------

Approval for conduct of the survey was obtained from ethics review boards and/or hospital administration in each country as required according to local guidelines. Return of a completed questionnaire was considered indicative of consent. Participants were advised that survey completion was voluntary. To maintain anonymity, no ICU or participant identifiers were collected.

A study investigator coordinated survey administration in each country. Surveys were distributed via mail in the UK and the Netherlands; by email in Denmark, Switzerland, Germany, Italy and Norway; and conducted by phone in Greece. In Germany a link to the survey was also advertised on professional websites. Country coordinators selected the survey delivery method based on available contact details. Three reminders to complete the survey were sent via mail, email or phone at two week intervals from initial distribution. Participants who received mail surveys were provided with a stamped-addressed envelope to return the survey to the coordinating center of that country. Email surveys were returned to the country coordinator (Denmark, Switzerland and Italy) or to a secure collector maintained by either Global Park <http://www.globalpark.com/> (Germany) or Questback <http://www.questback.com/> (Norway).

Statistical Methods
-------------------

We included data from incomplete questionnaires, therefore denominators for survey items vary. We excluded from analysis surveys with \> 50% incomplete items. We summarized categorical variables such as professional group responsible for ventilation decisions using proportions and their 95% confidence intervals (CI). We calculated relative risks to determine the ventilator settings most likely to be adjusted by nurses \> 50% of the time. The total scores for each of the two 0 to 10 scales used to measure perceived autonomy and nursing contribution to decision-making (0 represented no nurse autonomy and decision making input and 10 represented complete autonomy and nurse input into all decisions) were calculated and the median and interquartile range (IQR) determined.

Relevant variables selected *a priori*(country, nurse-to-patient ratio, presence of a protocol, hospital teaching status, number of ICU beds, and open versus closed model ICU) as likely to be associated with the professional group (collaborative compared to medical input only) most responsible for each of the six key decisions were examined using multiple logistic regression and odds ratios and their 95% CIs calculated. All models were assessed for collinearity and goodness of fit. All tests were two-tailed and we considered a *P*-value of 0.05 as statistically significant. Analyses were performed using SPSS 18.0 (SPSS, Chicago, IL, USA).

Results
=======

Response Rates and Unit Characteristics
---------------------------------------

Response rates ranged from 39% (UK) to 92% (Switzerland) providing 586 surveys for evaluation. We were unable to determine the participant denominator in Germany due to the recruitment methods used and therefore cannot report a response rate. Unit characteristics are shown in Table [1](#T1){ref-type="table"}. Germany had a higher proportion of ICUs with \> 8 beds and more open ICUs than other countries except Denmark. A 1:1 nurse-to-patient ratio was used almost exclusively (93% of ICUs) for invasively ventilated patients in the UK; 6% used either a 1:1 or 1:2 nurse-to-patient ratio dependent on patient acuity. Switzerland, Denmark and Norway employed a 1:1 nurse-to-patient ratio in the majority of ICUs (61%, 73% and 90%, respectively). In the remaining countries, a 1:2 nurse-to-patient ratio was most common. For patients receiving NIV, a 1:2 nurse-to-patient ratio was most common in Germany, Switzerland, Italy, the Netherlands and the UK. ICUs in Denmark and Norway used a 1:1 nurse-to-patient ratio and Greek ICUs a 1:3 ratio.

###### 

ICU Demographics

  ----------------------------------------------------------------------------------------------------------------------------------------
                                   Switzerland\   UK\          Germany\     Netherlands\   Denmark\    Greece\     Norway\     Italy\
                                   (*n*= 73)      (*n*= 115)   (*n*= 201)   (*n*= 71)      (*n*= 41)   (*n*= 12)   (*n*= 39)   (*n*= 34)
  -------------------------------- -------------- ------------ ------------ -------------- ----------- ----------- ----------- -----------
  Hospital type                                                                                                                

   Private                         6 (6)          \-                        \-             \-          \-          \-          \-

   University affiliated           11 (15)        71 (62)      64 (32)      3 (4)          22 (54)     5 (42)      11 (28)     1 (3)

   Community/cantonal (teaching)   47 (64)        18 (16)      135 (67)     43 (61)        9 (22)      3 (25)      28 (72)     23 (68)

   Community/cantonal\             9 (12)         21(18)       \-           22 (31)        10 (24)     4 (33)      \-          10 (29)
  (non-teaching)                                                                                                               

  ICU specialty                                                                                                                

   Med/surg/trauma                 34 (47)        59 (51)      49 (24)      29 (41)        15 (37)     5 (42)      18 (46)     21 (62)

   Medical/surgical                26 (36)        36 (31)      50 (25)      33 (47)        16 (39)     3 (25)      12 (31)     4 (12)

   Medical (only)                  5 (7)          \-           38 (19)      \-             2 (5)       \-          2 (5)       2 (6)

   Surgical (only)                 3 (4)          3 (3)        24 (12)      2 (3)          \-          \-          3 (8)       2 (6)

   Cardiothoracic                  1 (1)          8 (7)        14 (7)       1 (1)          3 (7)       4 (33)      1 (3)       4 (12)

   Neuro/trauma                    3 (4)          4 (4)        15 (8)       2 (3)          2 (5)       \-          1 (3)       \-

   Neurosurgery (only)             1 (1)          \-           5 (3)        \-             3 (7)       \-          1 (3)       \-

   Burns                           \-             1 (1)        1 (1)        \-             \-          \-          1 (3)       \-

  ICU type                                                                                                                     

   closed                          66 (90)        97 (84)      142 (71)     44 (62)        9 (22)      7 (58)      30 (77)     32 (94)

   open                            6 (8)          12 (10)      56 (28)      15 (21)        22 (54)     3 (25)      8 (21)      1 (3)

  ICU bed numbers                                                                                                              

   ≤8 beds                         44 (60)        59 (51)      36 (18)      34 (48)        19 (46)     5 (42)      25 (64)     28 (82)

   9-16 beds                       18 (25)        31 (27)      116 (58)     26 (37)        11 (27)     6 (50)      7 (18)      6 (18)

   ≥17 beds                        7 (10)         16 (21)      48 (24)      9 (13)         8 (20)      1 (8)       5 (13)      
  ----------------------------------------------------------------------------------------------------------------------------------------

All data are n (%). Percentages may not add up to 100% due to missing data or rounding. Med, medical; n, number; surg, surgical.

Decisional Responsibility
-------------------------

Interprofessional responsibility for six key ventilation and weaning decisions is shown by country in Table [2](#T2){ref-type="table"}. Interprofessional collaboration was the most common approach for all decisions regarding (n/N, % (95% CI)) initial selection of ventilator settings (365/584, 63% (59-66)), determination of extubation readiness (414/581, 71% (67-75)), weaning method (423/583, 73% (69-76)), recognition of weaning failure (489/582, 84% (81-87)) and weaning readiness (496/585, 85% (82-87)), and titration of ventilator settings (515/582, 88% (86-91)). Despite interprofessional collaboration being least likely in the selection of initial ventilator settings, nurses collaborated in this decision in \> 75% of respondent ICUs in Switzerland, Germany and the UK.

###### 

Responsibility for Ventilation Decisions by Country

  ------------------------------------------------------------------------------------------------------------------------------------------
                                     Switzerland\   UK\          Germany\     Netherlands\   Denmark\    Greece\     Norway\     Italy\
                                     (*n*= 73)      (*n*= 115)   (*n*= 201)   (*n*= 71)      (*n*= 41)   (*n*= 12)   (*n*= 39)   (*n*= 34)
  ---------------------------------- -------------- ------------ ------------ -------------- ----------- ----------- ----------- -----------
  Initial ventilator settings                                                                                                    

   Physician only                    13 (18)        23 (20)      49 (24)      32 (45)        18 (44)     7 (58)      25 (64)     23 (68)

   Collaborative                     55 (85)        90 (78)      134 (67)     40 (56)        22 (54)     5 (42)      14 (36)     11 (32)

   Nurse only                        4 (6)          1 (1)        18 (9)       \-             \-          \-          \-          \-

   Other                             1 (1)          \-           \-           1 (1)          \-          \-          \-          \-

  Titration of ventilator settings                                                                                               

   Physician only                    3 (4)          \-           8 (4)        3 (4)          2 (5)       1 (8)       3 (8)       15 (44)

   Collaborative                     63 (86)        112 (99)     176 (88)     66 (93)        37 (90)     11 (92)     34 (87)     19 (56)

   Nurse only                        5 (6.8)        1 (1)        15 (8)       2 (3)          1 (2)       \-          2 (5)       \-

   Other                             2 (3)          1 (1)        \-           \-             \-          \-          \-          \-

  Readiness to wean                                                                                                              

   Physician only                    5 (7)          4 (4)        25 (12)      11 (16)        1 (2)       8 (67)      7 (18)      18 (53)

   Collaborative                     65 (89)        111 (97)     172 (82)     59 (83)        39 (95)     4 (33)      32 (82)     16 (47)

   Nurse only                        2 (3)          \-           3 (2)        \-             \-          \-          \-          \-

   Other                             1 (1)          4 (4)        \-           1 (1)          \-          \-          \-          \-

  Weaning method                                                                                                                 

   Physician only                    5 (7)          10 (9)       37 (18)      20 (28)        10 (24)     6 (50)      11 (28)     25 (74)

   Collaborative                     59 (81)        104 (90)     131 (71)     49 (69)        31 (76)     6 (50)      27 (69)     9 (27)

   Nurse only                        4 (6)          \-           22 (11)      1 (1)          \-          \-          \-          \-

   Other                             5 (7)          6 (5)        \-           1 (1)          \-          \-          \-          \-

  Readiness to extubate                                                                                                          

   Physician only                    17 (23)        15 (13)      45 (22)      35 (49)        9 (22)      7 (58)      13 (33)     20 (59)

   Collaborative                     56 (77)        98 (85)      152 (76)     36 (49)        32 (78)     5 (42)      25 (64)     14 (41)

   Nurse only                        \-             \-           2 (1)        \-             \-          \-          \-          \-

   Other                             \-             2 (2)        \-           \-             \-          \-          \-          \-

  Weaning failure                                                                                                                

   Physician only                    7 (10)         2 (2)        13 (7)       7 (10)         4 (10)      6 (50)      6 (15)      12 (35)

   Collaborative                     65 (89)        105 (91)     169 (85)     57 (80)        37 (90)     6 (50)      32 (82)     21 (62)

   Nurse only                        1 (1)          5 (4)        17 (9)       3 (4)          \-          \-          \-          \-

   Other                             \-             2 (2)        \-           4 (6)          \-          \-          \-          \-
  ------------------------------------------------------------------------------------------------------------------------------------------

All data are n (%). Note some % do not add to 100 due to missing data. Other: includes physiotherapists or specialized ventilator practitioners who may also hold a nursing qualification. n, number

A nurse-to-patient ratio other than 1:1 was associated with decreased interprofessional collaboration (decisions made independently by physicians without nursing input) during titration of ventilator settings (OR 0.2 (95% CI 0.1-0.6)), weaning method (0.4 (0.2-0.9)), determination of extubation readiness (0.5 (0.2-0.9)) and weaning failure (0.4 (0.1-1.0)) when controlling for country, ICU type (open versus closed), ICU size, presence of a protocol, and hospital teaching status. Use of a ventilator protocol or guideline was associated with increased collaborative decision making (communication between physicians and nurses) for weaning (OR 1.8 (95% CI 1.0-3.3)) and extubation readiness (1.9 (1.2-3.0)) and weaning method (1.8 (1.1-3.0)) when controlling for the same variables. Country of ICU location influenced the profile of professional responsibility for all decisions. Nurses were least likely to be involved in any type of ventilator decision making in ICUs located in Greece and Italy and most likely to be involved in Switzerland and the UK. Nurses were independently (without consulting a physician) responsible for titration of Fraction of inspired oxygen (FiO~2~) and pressure support in most ICUs (Table [3](#T3){ref-type="table"}). In the majority of ICUs in Switzerland, Germany and the UK, nurses independently titrated all ventilator settings including change of mode except the level of positive end expiratory pressure (PEEP). Nurses rarely independently titrated ventilator settings in Italy and Greece.

###### 

Type of Ventilator Settings made independently by Nurses\*

                                      n/N       \% (95% CI)   RR (95% CI)
  ----------------------------------- --------- ------------- ----------------
  Decrease of FiO~2~                  392/580   68 (64-71)    1
  Increase of FiO~2~                  386/580   67 (63-70)    1.0 (0.9-1.1)
  Increase of pressure support        321/582   55 (51-59)    0.8 (0.7-0.9)
  Decrease of pressure support        317/580   55 (51-59)    0.8 (0.7-0.9)
  Titration of respiratory rate       290/581   50 (46-54)    0.7 (0.7 -0.8)
  Titration of tidal volume           251/576   44 (40-48)    0.6 (0.6-0.7)
  Titration of inspiratory pressure   229/577   40 (36-44)    0.6 (0.5-0.7)
  Change mode                         231/583   40 (36-44)    0.6 (0.5-0.7)
  Decrease of PEEP                    162/579   28 (25-32)    0.4 (0.4-0.5)
  Increase of PEEP                    147/581   25 (22-29)    0.4 (0.3-0.4)

\*Nurse responsible to make and implement ventilator setting change independent \> 50% of the time.

CI, confidence interval; RR, relative risk; FiO~2~, fraction of inspired oxygen; number; PEEP, positive end expiratory pressure.

Automated Closed Loop Systems and Ventilation Protocols
-------------------------------------------------------

Of the 586 ICUs, 319 (55% \[50-59\]) indicated they used SmartCare/PS, ASV, PAV or MMV. More ICUs reported using ASV \> 50% of the time than other automated weaning systems (Figure [1](#F1){ref-type="fig"}). Protocols for ventilation (54% in the UK to 81% in Switzerland) and weaning (56% in Italy to 69% in Switzerland) were used in most ICUs in all countries with the exception of Greece where no ICU reported a protocol for management of ventilation and only one ICU reported availability of a weaning protocol. Availability of protocols for NIV ranged from 1 in 12, 8% (Greece) to 62 in 71, 87% (Netherlands) ICUs.

![**Use of Automated Closed Loop Systems**.](cc10588-1){#F1}

Nurse Autonomy, Influence and Ventilator Education
--------------------------------------------------

Nurse managers\' ratings of nurse autonomy and influence on decision making about mechanical ventilation practices ranged from 0 (no autonomy or influence) to 10 (complete autonomy and always influenced decisions) with a median score of 7 for both scales. Autonomy was rated highest by Swiss nurse managers (median 8, IQR 6 to 8) and lowest by those from Greek ICUs (5, 5 to 7). Ratings of nurse influence in ventilation decision making were similar across all countries. Most ICUs in all countries provided education related to ventilation to nurses during commencement of employment (65% in Italy \[lowest\] to 98% in the UK \[highest\]).

Discussion
==========

Our findings indicate, according to nurse managers, that interprofessional collaboration was the predominant model for decisions about mechanical ventilation and weaning and nurses generally had a reasonable influence on decisions made. Interprofessional collaboration varied according to the type of decision with physicians more likely to select initial ventilator settings and nurses more involved in the ongoing titration of ventilation and determination of extubation readiness. To the best of our knowledge, this is the largest survey describing interprofessional role responsibility for mechanical ventilation across Europe. Our findings suggest greater involvement of nurses in ventilator adjustment compared to a previous survey of physicians profiling ICU nursing in Western Europe conducted over a decade ago \[[@B14]\] but congruence in some countries with interprofessional responsibility for ventilation decisions in Australia and New Zealand \[[@B5]\] and participation in weaning practices reported in a pilot study of European nurses \[[@B19]\]. Physicians are generally present during initiation of ventilation as it coincides with intubation or arrival in ICU and represents an acute deterioration in respiratory status. ICU nurses maintain a near continuous presence at the bedside and therefore may be best positioned to titrate ventilator settings in response to changes in physiologic parameters.

Interprofessional collaboration for ventilation decision making varied by country with nursing input into ventilation decisions highest in Switzerland, Germany, and the UK and lowest in Greece and Italy. Irrespective of country, collaboration was influenced by nurse-to-patient ratio and the presence of protocols. Variation in the degree of collaboration is likely due to organizational, professional, and systemic factors that create power differences and delineate role responsibility \[[@B20]\]. The clinical implications of this variation in collaborative decision making on patient outcomes such as the duration of ventilation and weaning is unclear. However, several randomized controlled trials of either weaning or sedation protocols attribute the lack of reduction in ventilation duration to the existing organizational context including high staffing ratios, nurse autonomy in decision making and frequency of medical rounds that influence the usual care arm of the trial \[[@B21]-[@B23]\]. The absence of interprofessional collaboration has the potential to result in delayed adaptation of ventilation to changing physiological parameters, and delayed recognition of weaning and extubation readiness resulting in unnecessary prolongation of ventilation. High levels of interprofessional collaboration have previously been associated with low standardized mortality ratios (SMR) \[[@B3]\] and lower rates of ICU readmission following ICU discharge \[[@B24],[@B25]\]; whereas ineffective interprofessional collaboration has been associated with the development of ventilator associated pneumonia and pressure ulcers \[[@B26]\], poor team functioning, morale \[[@B27]\] and ethical decision making \[[@B28]\]. Further studies are required to examine the impact of interprofessional collaboration on potentially modifiable outcomes such as weaning duration.

The utility of nurse involvement in ventilator decision making is reliant on appropriate knowledge and skills to manage ventilation. Differences existed in the proportion of ICUs providing education related to mechanical ventilation across countries, most probably as a reflection on the role of nurses in ventilation and weaning. On a broader level, differences also exist in the type and content of critical care nursing education internationally \[[@B29]\] that likely impact nurse involvement and autonomy. Furthermore, in ICUs with lower nurse-to-patient ratios, nurses may not be available for ventilator decision making due to the demands of ongoing assessment and provision of care to more than one patient.

Our findings suggest that nurses were more likely to make and implement decisions related to weaning, such as titration of pressure support and FiO~2~, independently. Nursing involvement in weaning has increased over the past two decades with the introduction of weaning protocols. Although, as discussed above, the effect of weaning protocols may be moderated by contextual factors \[[@B30]\] and no study has identified harm associated with nursing involvement in the weaning process. Interestingly, the level of PEEP was the ventilator setting least likely to be independently adjusted by nurses. While we did not seek information on the rationales for nurse initiated ventilator titration, we hypothesize that knowledge required to adjust PEEP may be viewed as more complex or that PEEP adjustment is perceived to pose greater risk of adverse consequences, although the logic of this viewpoint is questionable given the evidence of harm related to high tidal volume ventilation \[[@B31]\].

This study, to the best of our knowledge, is the first to report insight into the use of automated weaning systems in practice. Though just over 50% of ICUs reported using one or more automated closed loop system, few ICUs in all countries used them routinely. The goal of automated weaning systems is to improve adaptation of ventilatory support to the patients\' needs through continuous monitoring and real-time interventions \[[@B17]\]. Several randomized controlled trials describe a reduction in duration of mechanical ventilation using automated weaning \[[@B32]-[@B34]\] while others demonstrate no effect \[[@B23],[@B35]\]. As technology advances and the evidence about the utility of these systems increases, it is important to continue to track adoption into practice.

Our study has several limitations including the potential for selection bias, self-report bias, confounding, and lack of generalizability. Nurse managers interested in the delineation of interprofessional responsibilities for mechanical ventilation were probably more likely to respond to this questionnaire. As we chose to survey nurse managers, nurses\' roles with respect to ventilation and weaning may be over-represented despite our instruction to confer with senior medical and nursing colleagues. There is also the possibility that other contextual factors not measured in our survey contributed to decisional responsibility. Lack of generalizability is particularly problematic regarding survey responses from Greece and Italy as only certain regions of these countries were surveyed.

Conclusion
==========

Our cross-sectional survey of nurse managers suggests that collaborative decision making for important decisions related to ventilation and weaning was employed in most ICUs in all countries. Nurse-to-patient ratio, availability of protocols and country influenced nurse involvement in decision making. Further study is warranted to determine if collaborative decision making is associated with improved patient outcomes for mechanically ventilated patients.

Key messages
============

• interprofessional collaboration was the predominant model for decisions about mechanical ventilation and weaning

• interprofessional collaboration for ventilation decision making varied by country and was modified by nurse-to-patient ratio and the presence of protocols

• more than 50% of ICUs reported using one or more automated closed loop system, few ICUs in all countries used them routinely

• variation exists in the adoption of protocols for ventilation and weaning

Abbreviations
=============

ASV: adaptive support ventilation; CI: confidence interval; ICU: intensive care unit; IQ: interquartile range; MMV: mandatory minute ventilation; NIV non invasive ventilation; OR: odds ratio; PAV: proportional assist ventilation; PEEP: positive end expiratory pressure.

Competing interests
===================

The authors declare that they have no competing interests.

Authors\' contributions
=======================

LR, MJS, PS, IE, BB, HH conceived the study. BB, DM, IE, HH, JH, MI, KK, MS, RS coordinated data collection and data entry in their own countries. LR collated and analyzed the data. All authors contributed to manuscript drafts and have read and approved the final manuscript.

Supplementary Material
======================

###### Additional file 1

**Survey of Ventilation and Weaning Responsibility**. Generic version of the survey in English.

###### 

Click here for file

Acknowledgements
================

The authors thank Catherine Kelly, Mette Juel Blichfeldt, Anouk Kanitz, and Aly Hovingh for their assistance in the completion of this study.