Skip to main content
NCBI home page
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2025 Jan 22;81(9):5973–5983. doi: 10.1111/jan.16752

Planned Changes to Nurse Leadership, Staffing and Skill‐Mix: Impact on the Working Environment, Job Satisfaction and Intention to Leave

Noeleen Brady 1,✉, Selena O'Connell 1, David Gilligan 1, Caoimhe Madden 2, Lisa Gannon 1, Victoria Howson 1, Jane E Ball 3, Aileen Murphy 1, Peter Griffiths 3, Christine Duffield 4, P Anne Scott 2, Vera J C Mc Carthy 1, Jonathan Drennan 1,5
PMCID: PMC12371854  PMID: 39844513

ABSTRACT

Introduction

Job satisfaction and intention to leave have been consistently linked to the working environment. However, there are few studies of interventions for improving the environment or staff outcomes.

Aim

To determine the impact of implementing a framework for safe nurse staffing on the environment and staff outcomes. This involved an assessment of required nursing hours per patient day, supernumerary nurse in charge and minimum 80:20 skill‐mix, with intentional changes in staffing if required.

Design

A pre‐post observational design.

Methods

This was a prospective observational study in six medical and/or surgical wards across three acute hospitals in Ireland. The outcomes were measured pre‐ and post‐implementation, and included the environment, using the Practice Environment Scale of the Nursing Work Index; and job satisfaction and intention to leave using a dichotomised 4‐point scale.

Outcomes

Changes in staffing levels, adjustments to skill‐mix and the supervisory role of the ward leader were seen following the implementation. A multilevel model found significant increases over time on three of the five Nursing Work Index subscales: Staffing and Resource Adequacy, Collegial Nurse‐Physician Relations, and Nurse Participation in Hospital Affairs. Job satisfaction increased and intention to leave decreased, although the differences were not statistically significant. Increased job satisfaction was significantly associated with Staffing and Resource Adequacy, Collegial Nurse Physician Relations and Nurse Manager, Leadership and Support. A decreased odds of intention to leave was associated with increased job satisfaction.

Conclusion

There were significant improvements in the environment following the implementation of the Framework. Three of the practice environment subscales were significantly associated with job satisfaction, while job satisfaction is a predictor of intention to stay. This study indicates that intentional changes to staffing can result in improvements to working environments which may in turn have an impact on job satisfaction and furthermore, on intention to stay.

Impact

This study investigated intentional changes to nurse staffing in medical and surgical wards, examining the impact pre‐ and post‐implementation. This study underlined that when staffing is based on a systematic approach, based on a Framework for Safe Nurse Staffing, a subsequent improvement can be seen in staff's perceptions of the work environment, along with improvements in staff outcomes. This research will impact on staff working in acute settings as a means of determining staffing and improving outcomes using a Framework for Safe Nurse Staffing.

Reporting Method

STROBE checklist.

Patient or Public Contribution

No patient or public contribution.

Keywords: adult inpatient setting, intention to leave, intentional changes, job satisfaction, medical and surgical wards, pre‐post study, safe staffing, skill‐mix, working environment

Summary.

  • What does this paper contribute to the wider global clinical community?
    • ○
      Information on how to staff medical and surgical wards based on patient acuity and dependency are discussed in this paper referencing the Framework for Safe Nurse Staffing and Skill‐Mix in General and Specialist Medical and Surgical Care Settings in Adult Hospitals.
    • ○
      Staffing medical and/or surgical wards using a systematic approach can lead to a more positive working environment and better staff outcomes, such as job satisfaction.

1. Introduction

The practice environment is conceptualised as the interaction between the climate and culture of the organisation, and it has been identified that, when nursing staff work in an environment that ‘facilitates professional nursing practice’, this results in better outcomes for both patients and staff (Lake and Friese 2006: 2). The outcomes associated with a practice environment that is perceived as positive by staff includes increased nurse retention and lower rates of staff turnover, higher levels of job satisfaction as well as enhanced quality of care delivered to patients (Lake and Friese 2006; Dutra and Guirardello 2021; Muir et al. 2023).

There are a number of factors associated with nurse perceptions of a good working environment including ward leadership, collaboration with colleagues, nurse autonomy, control over the working environment and levels of nurse staffing (Paguio, Yu, and Su 2020; Labrague et al. 2022). A number of studies have reported an association with levels of nurse staffing and nurses' perceptions of the quality of their working environment (Lake and Friese 2006; Pursio et al. 2021; Wynendaele, Willems, and Trybou 2019). An important factor for a positive working environment is suitable staffing levels, which in turn leads to better autonomy (Pursio et al. 2021) and better staff outcomes (Wynendaele, Willems, and Trybou 2019).

The quality of the practice environment has also been associated with levels of job satisfaction and retention of nurses; an issue that is gaining increasing attention due to the projected shortfall in the nursing workforce to meet patient demand (Buchan, Catton, and Shaffer 2022). The components of a good practice environment have been associated with a reduction in intention to leave and enhanced job satisfaction among the nursing workforce (Aiken et al. 2024). Leone et al. (2015), following a replication of the RN4Cast study (Sermeus et al. 2011) in Portugal, reported that intention to leave due to job dissatisfaction was higher when nurses are more dissatisfied with the lack of opportunities for career advancement, had lower levels of participation in hospital affairs and worked in units with poorer staffing levels. It is also reported that the working environment for nurses (Staffing and Resource Adequacy, Nurse Manager Ability, Leadership and Support, and Collegial Nurse‐Physician relations) can account for burnout in nurses as well as intention to leave (Hämmig 2018; Dall'Ora et al. 2020). In addition, job stress has been identified as a critical factor for turnover rates and intention to leave (Lo et al. 2018). As the pressure on nursing staff continues to rise due to increasing healthcare demands, effective interventions are needed to increase job satisfaction for nurses, potentially reducing turnover and thus enhancing retention and recruitment of staff (Lo et al. 2018).

Modification of the working environment of nurses has been identified as one factor that can contribute to the retention and job satisfaction of this cohort of the health workforce. Leineweber et al. (2016) concluded from an analysis of the RN4Cast data that measures aimed at improving the practice environment would be a promising approach for the improvement of retention rates in European hospitals. In addition, the modifiability of the environment could not only stabilise the workforce but also reduce burnout and reduce the number of staff members intending to leave their position (Dall'Ora et al. 2020). Changes suggested to modify the practice environment included: implementing models of leadership, team structures, staff support and levels of staffing (Drennan et al. 2018; Sermeus et al. 2022; Aiken et al. 2024). However, the evidence is relatively limited on the association between changes to staffing and perceptions of the practice environment. An issue in exploring the association between nurse staffing and the practice environment is that the majority of studies in this area are cross‐sectional or observational in design; however, the evidence is consistent in that increased nurse staffing is associated with enhanced patient, nurse and organisational outcomes (Griffiths et al. 2016; Butler et al. 2019; Dall'Ora et al. 2022). Despite this, there remains limitations in the designs used (Griffiths et al. 2016; Drennan et al. 2018; Butler et al. 2019) with calls for before‐and‐after or interrupted time series designs to be applied (Shekelle 2013).

2. Background

To address the issues related to staff retention and recruitment, and to facilitate improvements in the clinical practice environment, the Department of Health in Ireland published a document titled A Framework for Safe Nurse Staffing and Skill Mix in General and Specialist Medical and Surgical Care Settings in Adult Hospitals in Ireland (henceforth referred to as the Framework) (Department of Health 2018). This policy document drew upon a decade of evidence on safe nurse staffing and skill‐mix levels in hospital wards (Sermeus et al. 2011; Twigg et al. 2012; Griffiths et al. 2016, 2019). Based on this Framework, a number of recommendations were made including that the majority of the skill‐mix in medical and surgical wards is comprised of registered nurses, the ward leader (clinical nurse manager) is 100% supervisory and that the staffing levels are determined by a systematic approach that is based on patient acuity and dependency levels; in this case the introduction of nursing hours per patient day to determine staffing requirements. Ensuring the nurse ward leader is not responsible for a patient caseload and was 100% supervisory was based on the premise that if effective leadership is not in place, increasing staffing levels will not enhance the working environment for staff (Aiken et al. 2011) as well as evidence on the association between clinical leadership and increased staff and patient satisfaction (Bender et al. 2012).

The recommendations in the Framework were initially implemented in six wards and were accompanied by a programme of research to measure the impact of planned changes to staffing on patient, nurse and organisational outcomes. This study reports on the results of the implementation of the recommendations in the Framework on the practice environment, job satisfaction and intention to leave the nursing workforce employed in the wards where the Framework was initially introduced.

3. The Study

3.1. Aim

The aim of this study was to measure the impact of the introduction of the recommendations of the Framework on the nursing practice environment, job satisfaction and intention to leave, along with exploring any associations between the nursing practice environment and staff outcomes (see Drennan et al. (2018) for further details on the study protocol).

3.2. Design

This study used a pre‐test/post‐test design where the outcomes were measured at two time points: pre‐test (T1), that is, prior to the implementation of the recommendations of the Framework, and post‐test, following the implementation of the recommendations of the Framework (T2).

There were three main recommendations in the Framework that were implemented in the wards:

  1. The introduction of nursing hours per patient day (NHpPD) to establish the staffing (registered nurses (RNs) and healthcare assistants (HCAs)) complement (detailed below).

  2. A skill‐mix ratio of 80:20 where 80% of the proportion of hours of care were delivered by registered nurses and 20% by healthcare assistants.

  3. The role of the Clinical Nurse Manager (the ward leader) to be 100% supervisory; that is the ward leader does not carry a patient caseload.

To estimate nurse staffing for each of the wards included in the study, the NHpPD staffing method was introduced; this approach was similar to that developed in Western Australia (Twigg and Duffield 2009). The staffing method grouped wards according to the levels of patient complexity, nursing interventions, number of beds and occupancy levels (see Department of Health 2018 for further details on calculations used). Actual and required NHpPD was measured on each of the wards over a six‐week period. Following this process, adjustments were made to both staffing levels and skill‐mix to meet the required NHpPD. The commercial workforce planning system, Trendcare, was used in estimating NHpPD (http://www.trendcare.com.au).

3.3. Sample

This study was carried out in six medical and surgical wards across three acute hospitals: one large acute university hospital (670 beds), one medium‐sized acute hospital (235 beds) and a small acute hospital (109 beds). The sampling method for the hospitals and wards was purposive and determined by the Department of Health based on a national survey which examined staffing levels in the hospitals in Ireland. All nursing staff employed on these wards (clinical nurse managers, RNs and HCAs) were the sample for the study and were invited to participate in the survey. Participation in survey was voluntary and participants consented at both T1 and T2. The exclusion criteria included any staff on maternity leave or extended sick leave at both timepoints; nursing students and agency staff on the wards were also excluded as these students are supernumerary to the staffing complement. The total sample size prior to the introduction of the recommendations in the Framework was n = 167 and n = 200 following the introduction.

3.4. Measures

A survey based on the RN4CAST study (Sermeus et al. 2011) was distributed to staff at T1 and T2. The staff survey included questions that asked staff to report on their demographic profile, years of experience, last shift worked, along with the Practice Environment Scale of the Nursing Work Index (PES‐NWI), and the measures of job satisfaction and intention to leave.

3.4.1. Practice Environment Scale of the Nursing Work Index

The PES‐NWI is a 31‐item instrument that measures five subscales of the work environment: Nurse Participation in Hospital Affairs, Nursing Foundations for Quality of Care, Nurse Manager Ability, Leadership, and Support, Staffing and Resource Adequacy and Collegial Nurse‐Physician Relations (Lake 2002). Items are scored on a four‐point Likert scale (strongly disagree to strongly agree) and mean scores are calculated for each domain with higher scores indicating a more favourable environment. The PES‐NWI has been used in other research to examine the association between staffing and the work environment (Duffield et al. 2009) and to compare changes in the practice environment of hospitals over time (Sermeus et al. 2022).

3.4.2. Job Satisfaction and Intention to Leave

Job satisfaction was measured using a single item that asked respondents to rate how satisfied they were with their current job in the hospital on a four‐point scale ranging from very dissatisfied to very satisfied. In relation to intention to leave, staff were also asked to indicate their future intention in the organisation by rating their probability of leaving their current job on a four‐point scale ranging from definitely will not leave, to definitely will leave. These measures were used to determine if there were any differences in nurse outcomes following the implementation of the recommendations of the Framework, along with determining any association between the subscales of the PES‐NWI and outcomes. Both of these measures were dichotomised into: satisfied (satisfied or very satisfied) or dissatisfied (dissatisfied or very dissatisfied); and intention to leave (definitely or probably will leave) or intention to stay (definitely or probably will not leave).

3.4.3. Nursing Hours per Patient Day (NHpPD)

To estimate nurse staffing for each of the wards included in the study, the NHpPD staffing method was introduced; this approach was similar to that developed in Western Australia (Twigg and Duffield 2009). The staffing method grouped wards according to the levels of patient complexity, nursing interventions, number of beds and occupancy levels (see Department of Health 2018 for further details on calculations used). Actual and required NHpPD was measured on each of the wards over a six‐week period. Following this process, adjustments were made to both staffing levels and skill‐mix to meet the meet the required NHpPD, taking into account the individual wards' average maternity leave and additional 20% for sickness absence and continuing professional development. The commercial workforce planning system, Trendcare, was used in estimating NHpPD (http://www.trendcare.com.au) and is the workload management tool currently in place in the acute hospital system in Ireland. This system has been identified as being a valid process for predicting the nursing resource for patient care (Plummer 2015); however, it has been noted that further research on workload management systems is required as they may not account for the totality or quality of care that patients and their families experience (Dewar et al. 2024; Pirret et al. 2024).

3.5. Reliability and Validity

Staff perceptions of the practice environment was measured by the Practice Environment Scale of the Nursing Work Index (PES‐NWI). The PES‐NWI has demonstrated good internal consistency in previous research with Cronbach's alpha reported to range from 0.70–0.98 (Lake and Friese 2006; Roche and Duffield 2010). In this study, the internal consistency of the scales of the PES‐NWI were measured at time 1 and time 2; all values at both timepoints were above or close to the recommended alpha values (Table S1). Job satisfaction was measured with a single‐item; the use of single‐item job satisfaction questions has been identified as having good convergent validity when compared to multi‐item job satisfaction scales and has been identified as an acceptable approach to measuring the construct (Fakunmoju 2020). Similarly, the single item questions, such as intention to leave, have been identified as having greater face validity and respondent acceptability in long surveys (Djurkovic, McCormack, and Casimir 2003), such as the one used in this study.

3.6. Procedure

Data were collected at ward level; this is different to a number of studies that have previously measured the association between staffing and the environment at hospital level and has been identified as the best approach to measuring outcomes associated with nurse staffing (Needleman et al. 2011; Griffiths et al. 2020). Survey design and distribution was informed by best practice in ensuring high response rates (Dillman, Smyth, and Christian 2014). Staff were pre‐informed by letters about the study, through meetings at ward and hospital level and information posted throughout the wards. Surveys were then hand delivered by the research team to nursing staff on the ward with staff offered the option of returning the survey to a box on the ward or posting it directly to the research team. Follow‐up for non‐returned surveys was conducted approximately halfway into the data collection period (Dillman, Smyth, and Christian 2014). Data were collected at two time points: T1 and T2; in T1 no changes to the ward complement were made. In T2, following the introduction of the recommendations in the Framework to the wards subsequent changes in the staffing complement, skill‐mix and the supervisory capacity was made on the wards. T1 occurred from July 2016 to January 2017, while T2 was October 2017 to January 2018.

3.7. Ethical Considerations

Ethical approval was obtained from the research ethics committees at each of the hospitals (Beaumont Hospital Ethics Committee, Reference: 16/53; North‐East Area Research Ethics Committee, REC/16/035). Data were pseudo‐anonymised between T1 and T2. Participants were matched between T1 and T2 by use of a code, which was stored in an encrypted file, on a secure server. Participants were informed, prior to participation, that there was a code matched to their name for the purpose of longitudinal analyses. Only the research team directly involved in the data collection and analyses had access to the code. The file that matched responses between T1 and T2 was destroyed upon completion of data collection, and all participants' data were anonymised.

3.8. Data Analysis

SPSS version 26 (IBM Corp. 2016) was used for all data analyses. Multivariable multilevel repeated measures models were used to analyse the association of Time with the PES‐NWI subscales. The subscales were nested at ward level as individuals rate the environment in a particular ward rather than at an individual level. Multilevel models with a categorical repeated measures outcome were used to analyse the association of Time and the PES‐NWI subscales on both job satisfaction and intention to leave, with the additional variable of job satisfaction as an explanatory factor for the latter. Respondents that did not complete the PES‐NWI and/or job satisfaction and intention to leave items were excluded from analyses. One respondent did not complete the PES‐NWI at T2. Three respondents did not complete the job satisfaction or intention to leave questions at T1; while one did not complete the job satisfaction question, and two did not complete the intention to leave questions at T2.

Following on from the guidelines for the interpretation of the PES‐NWI (Lake and Friese 2006: 4), values above 2.5 were related to general levels of agreement with scores below 2.5 indicating levels of disagreement that the concepts measured by the scales are present. In addition, wards scoring 2.5 or above on none or only one of the subscales were rated as unfavourable; ‘on two or three subscales as mixed; and on four or five subscales as favourable’. A p value of ≤ 0.05 was reported as being statistically significant.

4. Results

4.1. Implementation of the Recommendations in the Framework

The implementation of the safe staffing Framework resulted in a number of intentional changes to RN and HCA staffing. Based on NHpPD measures, four of the six wards required a change in staffing levels ranging from an increase of 3.5 whole time equivalents (WTEs) to 12.7 WTEs. There were also adjustments made to the skill‐mix in four of the six wards (wards 1, 2, 3 and 6), along with the adjustment of the ward leader (clinical nurse manager (CNM)) role to ensure that they were 100% supervisory. To ensure the supervisory status, the CNM post was not included in the calculation of the staffing requirements. The two remaining wards (wards 4 and 5) were shown to have the full staffing complement based on the required and available NHpPD measured at T1; thus, no uplift to staffing was made in these wards; however, it was identified that the role of the CNM 2 was 100% supervisory and the skill‐mix at the time of the study consisted of 80% RNs and 20% HCAs.

4.2. Response Rates

A total of n = 167 surveys were distributed during T1. During this time n = 19 members of nursing staff were on maternity leave, extended sick leave or had been transferred from the ward, leaving a total valid sample of n = 148. Following this, n = 47 did not respond providing a valid response rate of 68.2% (101/148) for T1. During T2, n = 200 surveys were distributed. Similarly, n = 21 staff were excluded due to maternity leave, extended sick leave or transfer from the ward. This resulted in a total valid sample of n = 179, of which n = 57 did not participate, giving a valid response rate of 68.2% for T2 (122/179). Maternity leave and sick leave accounted for a similar absence over the two timepoints.

4.3. Demographic Profile of the Sample

The majority of respondents were RNs at T1 (89.1%) and T2 (77.9%) with the average years qualified at T1 = 13.77 years (SD = 9.32) and 11.89 years (SD = 8.97) at T2. The majority of respondents at T1 (63.3%) and T2 (66.0%) were educated to bachelor's degree level (Table 1).

TABLE 1.

Profile of the respondents Time 1 and Time 2.

Characteristic Time 1 n (%) Time 2 n (%)
Participants (n) 101 122
Grade
RN 90 (89.1) 95 (77.9)
HCA 11 (10.9) 27 (22.1)
Gender
Female 94 (93.1) 105 (87.5)
Male 7 (6.9) 15 (12.5)
Highest education level (RN only)
Certificate 4 (4.4) 5 (5.3)
Diploma 15 (16.7) 10 (10.6)
Degree 57 (63.3) 62 (66.0)
PG Cert/Diploma 4 (4.4) 2 (2.1)
Masters 9 (10.0) 10 (10.6)
Experience
Years qualified (M, SD) 13.77 (9.32) 11.89 (8.97)
Years in current hospital (M, SD) 8.04 (6.33) 6.80 (6.67)
Years in current ward (M, SD) 7.33 (5.93) 5.83 (6.24)
Open in a new tab

4.4. Practice Environment

In T1, two of the subscales scored below the cut‐off score of 2.5 indicating an unfavourable environment on these subscales; these were: Staffing and Resource Adequacy and Nurse Participation in Hospital Affairs. Four of the five subscales in T2 were above the cut‐off score of 2.5 indicating a favourable environment, while Staffing and Resource Adequacy had greatly improved by 35% and was approaching the cut‐off of 2.5 (T1 = 1.78; T2 = 2.41). All wards in T1 rated Staffing and Resource Adequacy as unfavourable, while four of the six wards rated Nurse Participation in Hospital Affairs as unfavourable. Descriptive statistics for the five subscales, at both time points, at ward level, can be seen in the Table 2.

TABLE 2.

Overall PES‐NWI a scores Time 1 and Time 2 by ward.

Subscales Ward 1 b Ward 2 b Ward 3 b Ward 4 Ward 5 Ward 6
Time 1 Time 2 Time 1 Time 2 Time 1 Time 2 Time 1 Time 2 Time 1 Time 2 Time 1 Time 2
M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD)
Staffing and resource adequacy 1.57 (0.58) 2.23 (0.69) 1.72 (0.57) 2.83 (0.63) 1.85 (0.38) 2.86 (0.51) 1.42 (0.36) 1.89 (0.67) 1.94 (0.59) 2.11 (0.70) 2.11 (0.46) 1.95 (0.77)
Collegial nurse‐physician relations 2.85 (0.23) 3.11 (0.33) 2.62 (0.42) 2.96 (0.42) 2.75 (0.49) 2.98 (0.51) 2.09 (0.47) 2.70 (0.46) 2.89 (0.43) 2.76 (0.45) 3.05 (0.27) 2.94 (0.33)
Nurse manager ability, leadership and support of nurses 2.73 (0.44) 2.64 (0.44) 2.67 (0.46) 2.89 (0.56) 2.55 (0.55) 2.77 (0.62) 2.48 (0.36) 2.31 (0.59) 2.50 (0.27) 2.65 (0.41) 2.39 (0.49) 2.30 (0.68)
Nurse participation in hospital affairs 2.28 (0.44) 2.40 (0.48) 2.40 (0.46) 2.75 (0.41) 2.52 (0.50) 2.91 (0.43) 1.99 (0.39) 2.30 (0.54) 2.23 (0.46) 2.57 (0.46) 2.65 (0.29) 2.39 (0.61)
Nursing foundations for quality of care 2.72 (0.45) 2.72 (0.36) 2.82 (0.21) 3.03 (0.43) 2.83 (0.24) 3.02 (0.50) 2.52 (0.33) 2.55 (0.59) 2.74 (0.37) 2.97 (0.27) 2.92 (0.20) 2.77 (0.31)
Open in a new tab
a

Scale Scores Range from 1 to 4—higher scores indicate greater levels of agreement; lower scores indicate disagreement.

b

Wards 1, 2, and 3 received an uplift in staff; wards 4 and 5 staffing complement did not change; ward 6 received an adjustment in its skill‐mix.

Each of the subscales showed an improved upward trajectory from T1 to T2. This was particularly reported by respondents in perceived improvements in Staffing and Resource Adequacy (T1: 1.78–T2: 2.41), Nurse Participation in Hospital Affairs (T1: 2.37–T2: 2.61) and Collegial Nurse‐Physician Relations (T1: 2.75–T2: 2.96) (Table 2). While there was a less pronounced change, both PES‐NWI subscales of Nurse Manager Ability, Leadership and Support (T1: 2.56–T2: 2.64) and Nursing Foundations for Quality of Care (T1: 2.77–T2: 2.88) increased following the implementation of the Framework.

A multivariable multilevel model was used to determine the association between Time and the ratings of the practice environment for each five PES‐NWI scales, nested at ward level. There was significant variance within the subscales (F (5, 29) = 663.67, p ≤ 0.001) and significant variance in the PES‐NWI subscales growth model; that is, the interaction of the PES‐NWI subscales and Time (F (5, 487) = 14.11, p ≤ 0.001) warranting further investigation. The growth trajectories for each subscale are graphed at an overall (Figure S1), and individual ward level (Figure S2). Additional explanatory variables of gender and years of experience were added to the model; however, these were further excluded as they showed no significant associations with the PES‐NWI subscales, with the initial model depicting the most consistent results.

The model indicates that there is significant variation in each individual subscale, irrespective of Time: Staffing and Resource Adequacy (t (33) = 22, p ≤ 0.001; CI: 1.66–1.99); Collegial Nurse Physician Relations (t (34) = 32.90, p ≤ 0.001; CI: 2.56–2.90); Nurse Manager Ability, Leadership and Support (t (34) = 31.08, p ≤ 0.001; CI: 2.40–2.74); Nurse Participation in Hospital Affairs (t (34) = 28.81, p ≤ 0.001; CI: 2.22–2.55); Nursing Foundations for Quality of Care (t (33) = 33.51, p ≤ 0.001; CI: 2.59–2.92). The model also indicated that there was significant variability between the wards on the scores of the PES‐NWI subscales (Wald Z = 2.56, p < 0.05). However, the sample size at individual ward level is relatively small (n = 14–20), thus further regression modelling is not appropriate at individual ward level.

In the model, three of the five subscales showed significant change from T1 to T2, showing improvement on the subscales over time. Scores on Staffing and Resource Adequacy (t (749) = 7.70, p ≤ 0.001; CI: 0.41–0.69), Collegial Nurse Physician Relations (t (726) = 2.57, p ≤ 0.01; CI: 0.04–0.33) and Nurse Participation in Hospital Affairs (t (752) = 1.59, p ≤ 0.01; CI: 0.06–0.34) had significant interactions with Time with each score significantly increasing from T1 to T2 (Table 3).

TABLE 3.

Overall PES‐NWI a scores and multivariate multilevel model of the growth of the NWI‐PES subscales from T1 and T2 nested at ward level.

Characteristic Time 1 Time 2 t (p) b t (p) c
M (SD) M (SD) CI CI
Staffing and resource adequacy 1.78 (0.54) 2.41 (0.76) 22.09 (< 0.001) 7.70 (< 0.001)
1.66–1.99 0.41–0.69
Collegial nurse‐physician relations 2.75 (0.47) 2.93 (0.43) 32.90 (< 0.001) 2.57 (≤ 0.01)
2.56–2.90 0.04–0.33
Nurse manager ability, leadership and support of nurses 2.56 (0.45) 2.64 (0.60) 31.08 (< 0.001) 0.74 (0.46)
2.40–2.74 −0.09‐0.20
Nurse participation in hospital affairs 2.37 (0.46) 2.61 (0.52) 28.81 (< 0.001) 2.75 (< 0.01)
2.22–2.55 0.06–0.34
Nursing foundations for quality of care 2.77 (0.33) 2.88 (0.45) 33.51 (< 0.001) 1.59 (0.113)
2.59–2.92 −0.03‐0.25
Open in a new tab
a

Scale Scores Range from 1 to 4—higher scores indicate greater levels of agreement, lower scores indicate disagreement.

b

Variance within the NWI‐PES subscales.

c

Interaction between Time and the NWI‐PES subscales.

4.5. Nurse Outcomes and Associations With Changes in the Working Environment

4.5.1. Job Satisfaction

Overall, an increase was seen in the proportion of staff reporting that they were satisfied/very satisfied in T1 (53.1%) compared to satisfied/very satisfied at T2 (68.6%) (Table 4). Job satisfaction was dichotomised into satisfied or dissatisfied and multilevel models for repeated measures were carried out on job satisfaction using Time and the PES‐NWI subscales as the main explanatory variables. The four models carried out can be seen in the supplemental data (Table S2) while the final selected model will be discussed here. There was no significant effect for Time, years of experience or gender on job satisfaction. However, three of the PES‐NWI subscales were significantly associated with job satisfaction. Increasing scores on Staffing and Resource Adequacy (OR = 5.98; CI: 2.85–12.52), Collegial Nurse Physician Relations (OR = 3.49; CI: 1.05–11.63) and Nurse Manager Ability, Leadership and Support (OR = 2.92; CI: 1.05–8.16) significantly increased the odds of reported job satisfaction in participants. The PES‐NWI subscales were also aggregated at ward level however, there was no significant associations at this level (Table S2).

TABLE 4.

Job satisfaction and Intention to leave Time 1 and Time 2.

Characteristic Time 1 Time 2
(n) % (n) %
Job satisfaction (% reporting satisfied/very satisfied) 52 (53.1%) 83 (68.6%)
Intention to leave (% reporting probably/definitely will leave) 51 (52.0%) 56 (46.7%)
Open in a new tab

4.5.2. Intention to Leave

At T1, 52.0% of respondents reported that they will probably or definitely will leave their current job; this decreased to 46.7% in T2 following the introduction of the recommendations in the Framework. This measure was dichotomised into intention to stay/leave. Multilevel models with repeated measures were carried out to investigate the association between Time, years of experience and the PES‐NWI subscales on intention to leave. The final selected model will be discussed here but additional models are available in the supplemental data. There was no significant association between Time or the five PES‐NWI subscales on intention to leave. There was a significant effect for the control variable of gender and years of experience as a nurse, with males less likely to intend to leave than females (OR = 0.282; CI: 0.09–0.93) and years of experience as a nurse significantly negatively associated with intention to leave (OR = 0.916; CI: 0.89–0.95). Job satisfaction (satisfied) was significantly associated with a reduction in intention to leave (OR 0.158; CI: 0.8–0.33). (Table 5).

TABLE 5.

Final multilevel models for repeated measures of job satisfaction and intention to leave.

Job satisfaction Intention to leave
Odds ratio (p) Odds ratio (p)
Time 2 0.57 (0.197) 1.15 (0.669)
Years of experience 1.04 (0.169) 0.92 (< 0.001)
Gender (male) 2.79 (0.282) 0.282 (< 0.05)
Job satisfaction (satisfied) — 0.16 (< 0.001)
NWI‐PES
Staffing and resource adequacy 5.98 (< 0.001) —
Collegial nurse‐physician relations 3.49 (< 0.05) —
Nurse manager ability, leadership and support 2.92 (< 0.05) —
Nurse participation in hospital affairs 1.24 (0.750) —
Nursing foundations for quality of care 0.99 (0.989) —
Open in a new tab

5. Discussion

This is one of the few studies that have examined changes in the work environment of nursing staff and healthcare assistants following a planned change to nurse staffing. There were statistically significant improvements in respondent perceptions of Collegial Nurse‐Physician relations, Participation in Hospital Affairs and, particularly, Staffing and Resource Adequacy following the implementation of the recommendations of the Framework. These included the introduction of a systematic approach to determining nurse staffing levels, a skill‐mix that prioritises RNs and the enhancement of the supervisory role of the ward leader. The results also showed strong associations between Staffing and Resource Adequacy, Nurse Manager Ability, Leadership and Support, Collegial Nurse‐Physician Relations and job satisfaction, and separately job dissatisfaction and intention to leave.

Prior to the introduction of the recommendations in the Framework, all wards scored Staffing and Resource Adequacy as the least favourable aspect of the working environment in T1; although it remained the least rated of the PES‐NWI subscales in T2, the level of agreement increased significantly following the implementation of the initiative, although still scoring below the favourable cut‐off of 2.5. Based on Lake and Friese (2006), four of the five subscales were rated above 2.5 at T2 compared to a mixed rating at T1 (three of the five subscales above 2.5), indicating a more favourable working environment following the implementation of the Framework. The low ratings related to Staffing and Resource Adequacy at T1 may be a partial reflection in the reduction in the nursing workforce in Ireland that occurred as a consequence of the employment control framework initiated as a consequence of austerity measures during the recession (Williams and Thomas 2017); although there are still challenges, recent years have shown recovery in the numbers recruited to the nursing workforce with a 16.5% increase in the nursing workforce between 2019 and 2023 (Health Service Executive 2023). In addition, the regression analysis showed a strong relationship between Staffing and Resource Adequacy and job satisfaction. Staff members were 5.98 times more likely to report being satisfied with their job with each one‐point increase on this subscale. The association between better staffing and levels of job satisfaction has been identified in studies (Aiken et al. 2024), meta‐analyses (Shin, Park, and Bae 2018) and systematic reviews (Wynendaele, Willems, and Trybou 2019), where lower levels of nurse staffing are associated with an increase in job dissatisfaction.

Collegial Nurse‐Physician Relations and Participation in Hospital Affairs also significantly improved at T2 when compared to T1; previous studies have identified that excessive workloads due to staffing can be a barrier to effective communication between nurses and physicians (Burns 2011). Nurse Manager Ability, Leadership and Support was a particular target of the Framework by converting the clinical nurse manager role to 100% supervisory; however, no significant change in scores on this subscale were identified. While the change to the supervisory role did not result in changes on this scale, it is an important factor to measure and implementing a supervisory ward leader has a significant association with better staff and patient outcomes, namely job and patient satisfaction (Bender et al. 2012). A supervisory nurse leader role at ward level is identified as improving the delivery of care through enhancing healthcare team collaboration and coordination, thus while this subscale did not improve significantly, the addition of a supervisory nurse leader, may have impacted on other subscales, facilitating improvements in other aspects of the practice environment. Nurse Manager Ability, Leadership and Support of Nurses subscale decreased in three wards. This could be due to a number of factors, such as implementation challenges, negative attitudes and feelings, and the inconvenience of a new intervention (Välimäki et al. 2024).

When data were viewed at ward level (Table 2), the wards that showed the greatest change in PES‐NWI scores following the implementation of the Framework were generally those that received the greatest upward adjustment in RN and HCA staffing; this is consistent with a number of studies that have demonstrated that hospitals and wards with the most favourable nursing practice environment had better nurse to patient ratios (Lake and Friese 2006; Wynendaele, Willems, and Trybou 2019). Ward 6 was the exception to this pattern; this was due to a change in patient profile that became more dependent overtime, and while the staffing complement met the requirement at T1, due to this change, the staff complement was not able to meet the requirement at T2.

The proportion of staff in the previous RN4CAST survey in Ireland (37.7%) that reported that they intended to leave their current employment (Leineweber et al. 2016) was lower than that reported in this study, with over half of the respondents at T2 stating that they probably or definitely will leave. However, the results from the current study, are similar to recent data, showing that intention to leave across nurses in Europe was 33%, while Ireland specifically had 52% of nurses indicate their intention to leave due to job dissatisfaction (Aiken et al. 2024). This indicates that in last decade, there are a number of factors that are impacting on intention to leave (Maben and Bridges 2020). While the implementation of the recommendations of the Framework resulted in a greater number of staff reporting higher levels of job satisfaction, there was no significant impact on intention to leave their current position; this finding was identified despite the reported improvements in the working environment. This result is different to that highlighted in a meta‐analysis where poor staffing was associated with intention to leave (Shin, Park, and Bae 2018); however, Shin and colleagues reported that the effect size for job dissatisfaction was higher than intention to leave when measuring the association between nurses staffing and these nurse outcome measures. The strongest predictive factor for intending to leave a post was job dissatisfaction; a finding highlighted in a number of previous studies (Fasbender, Van der Heijden, and Grimshaw 2019; Leineweber et al. 2016). Additionally, there were fewer associations with intention to leave indicating that this present study did not capture the factor(s) influencing this outcome. It is possible that this measure was burnout, as previous research has shown strong associations between burnout and intention to leave the profession (Hämmig 2018; Dall'Ora et al. 2020).

Overall, the results of this study have identified that adjusting nurse staffing through implementing nursing hours per patient day to match patient need, implementing a supernumerary nurse leader, and an 80:20 skill‐mix, was associated with staff reporting an improvement in aspects of the work environment, and indicated positive patterns of change in job satisfaction and intention to leave, although not significant. The implementation of safe staffing levels is one organisational approach that can facilitate the retention of nurses (Aiken et al. 2024), a key factor in the current environment where recruitment is becoming increasingly challenging. In addition, the increase in the respondents' level of satisfaction as a result of the implementation of the Framework is a key indicator as it has been identified as being related to staff turnover (Fasbender, Van der Heijden, and Grimshaw 2019).

The results also address criticisms of the body of work in this field related to questions regarding the number of nurses required and what constitutes an appropriate skill‐mix (Van den Heede et al. 2020). The identification that the introduction of a Framework for Safe Nurse Staffing and Skill‐Mix in Medical, Surgical and Specialist Settings (Department of Health 2018) resulted in positive outcomes has now resulted its implementation on a phased basis to acute hospitals in Ireland. This roll‐out is an acknowledgement that structured approaches are required to improve patient, nurses and organisational outcomes. In relation to nursing outcomes, there is also acknowledgement that policy is required to enhance recruitment and retention (Van den Heede et al. 2020).

6. Conclusion

With some exceptions, few studies have reported on the outcomes following a planned change to nurse staffing and skill‐mix. This study, which measured the environment and staff outcomes, pre‐ and post‐introduction of (i) a systematic approach to determining nurse staffing levels, (ii) a skill‐mix that prioritises care provided by RNs and (iii) ensuring that the ward leader is in a fully supervisory capacity and does not have to undertake a clinical workload, addresses some of the criticism in this field that the majority of studies are predominantly observational. When nurse staffing levels are systematically adjusted to meet patient need there is an enhancement in staff perceptions of the working environment and job satisfaction, factors that result in higher levels of staff retention, an increasingly important issue as demand for nursing care in many countries increases. This study has since been expanded and a follow‐up is taking place to see if these results are sustainable and apparent in a larger sample.

7. Limitations

There are a number of limitations to the study. Respondents were asked their intention to leave rather than measure actual leave rates; therefore, intention may not be an accurate proxy for leaving an organisation. In addition, burnout was not measured as part of the research; this has been identified as being associated with intention to leave. There was a possibility that staff returning from sickness absence or other absences at T2 could have influenced the responses at T2; however, it was identified that the proportion of staff absent at T1 and T2 did not change, therefore this was not identified as a factor impacting on the overall results.

The TrendCare system is currently in place to determine Nursing Hours per Patient Day and although it has been identified as being valid in predicting direct nursing hours required in the Australian and New Zealand acute hospital sector (Plummer 2015), further testing is required within the Irish system.

As this was initially undertaken in six wards, sample size and number of wards was relatively small; however, as the Framework is now being rolled out on a national level in Ireland, this provides an opportunity to undertake longitudinal measures of the impact of planned change to staffing level, which is currently ongoing. This study addresses the criticism that the majority of the studies that explore the relationship between nurse staffing, skill‐mix and outcomes are cross‐sectional.

Author Contributions

The authors made substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data; N.B., S.O.C., D.G., C.M., L.G., V.H., J.B., P.G., C.D., P.A.S. and J.D. were involved in drafting the manuscript or revising it critically for important intellectual content; N.B., V.H., A.M., V.J.C.M., J.D., P.G. and S.O.C. gave final approval of the version to be published. Each author should have participated sufficiently in the work to take public responsibility for appropriate portions of the content; N.B., S.O.C., D.G., C.M., L.G., V.H., J.B., P.G., C.D., P.A.S., J.D., A.M. and V.J.C.M. agreed 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.

Conflicts of Interest

The authors declare no conflicts of interest.

Peer Review

The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer‐review/10.1111/jan.16752.

Statistics

The authors have checked to make sure that our submission conforms as applicable to the Journal's statistical guidelines. There is a statistician on the author team, Professor Jonathan Drennan. The author(s) affirm that the methods used in the data analyses are suitably applied to their data within their study design and context, and the statistical findings have been implemented and interpreted correctly. The author(s) agrees to take responsibility for ensuring that the choice of statistical approach is appropriate and is conducted and interpreted correctly as a condition to submit to the Journal.

Supporting information

Data S1.

JAN-81-5973-s001.docx (197KB, docx)

Data S2.

JAN-81-5973-s002.docx (20.7KB, docx)

Acknowledgements

Open access funding provided by IReL.

Funding: This work was supported by Department of Health and the Health Research Board, FSN‐2017‐001.

Data Availability Statement

Author elects to not share data.

References

  1. Aiken, L. H. , Cimiotti J. P., Sloane D. M., Smith H. L., Flynn L., and Neff D. F.. 2011. “Effects of Nurse Staffing and Nurse Education on Patient Deaths in Hospitals With Different Nurse Work Environments.” Medical Care 49, no. 12: 1047–1053. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Aiken, L. H. , Sermeus W., McKee M., et al. 2024. “Physician and Nurse Well‐Being, Patient Safety and Recommendations for Interventions: Cross‐Sectional Survey in Hospitals in Six European Countries.” BMJ Open 14, no. 2: e079931. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bender, M. , Connelly C. D., Glaser D., and Brown C.. 2012. “Clinical Nurse Leader Impact on Microsystem Care Quality.” Nursing Research 61: 326–332. [DOI] [PubMed] [Google Scholar]
  4. Buchan, J. , Catton H., and Shaffer F.. 2022. “Sustain and Retain in 2022 and Beyond.” Int. Counc. Nurses 71: 1–71. [Google Scholar]
  5. Burns, K. 2011. “Nurse‐Physician Rounds: A Collaborative Approach to Improving Communication, Efficiencies, and Perception of Care.” Medsurg Nursing 20, no. 4: 194–199. [PubMed] [Google Scholar]
  6. Butler, M. , Schultz T. J., Halligan P., et al. 2019. “Hospital Nurse‐Staffing Models and Patient‐ and Staff‐Related Outcomes.” Cochrane Database of Systematic Reviews 4: CD007019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Dall'Ora, C. , Ball J., Reinius M., and Griffiths P.. 2020. “Burnout in Nursing: A Theoretical Review.” Human Resources for Health 18: 1–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Dall'Ora, C. , Saville C., Rubbo B., Turner L., Jones J., and Griffiths P.. 2022. “Nurse Staffing Levels and Patient Outcomes: A Systematic Review of Longitudinal Studies.” International Journal of Nursing Studies 134: 104311. [DOI] [PubMed] [Google Scholar]
  9. Department of Health . 2018. Framework for Safe Nurse Staffing and Skill Mix in General and Specialist Medical and Surgical Care Settings in Adult Hospitals in Ireland. Dublin: Department of Health. [Google Scholar]
  10. Dewar, J. , Cook C., Smythe E., and Spence D.. 2024. “An Analysis of Time Conceptualisations and Good Care in an Acute Hospital Setting.” Nursing Inquiry 31, no. 2: e12613. [DOI] [PubMed] [Google Scholar]
  11. Dillman, D. A. , Smyth J. D., and Christian L. M.. 2014. Internet, Phone, Mail, and Mixed‐Mode Surveys: The Tailored Design Method. Hoboken, New Jersey: John Wiley & Sons. [Google Scholar]
  12. Djurkovic, N. , McCormack D., and Casimir G.. 2003. “The Physical and Psychological Effects of Workplace Bullying and Their Relationship to Intention to Leave: A Test of the Psychosomatic and Disability Hypotheses.” International Journal of Organization Theory & Behavior 7, no. 4: 469–497. [Google Scholar]
  13. Drennan, J. , Duffield C., Scott A. P., et al. 2018. “A Protocol to Measure the Impact of Intentional Changes to Nurse Staffing and Skill‐Mix in Medical and Surgical Wards.” Journal of Advanced Nursing 74, no. 12: 2912–2921. [DOI] [PubMed] [Google Scholar]
  14. Duffield, C. , Roche M., O'Brien‐Pallas L., Catling‐Paull C., and King M.. 2009. “Staff Satisfaction and Retention and the Role of the Nursing Unit Manager.” Collegian 16, no. 1: 11–17. [DOI] [PubMed] [Google Scholar]
  15. Dutra, C. K. D. R. , and Guirardello E. D. B.. 2021. “Nurse Work Environment and Its Impact on Reasons for Missed Care, Safety Climate, and Job Satisfaction: A Cross‐Sectional Study.” Journal of Advanced Nursing 77, no. 5: 2398–2406. [DOI] [PubMed] [Google Scholar]
  16. Fakunmoju, S. B. 2020. “Validity of Single‐Item Versus Multiple‐Item Job Satisfaction Measures in Predicting Life: Satisfaction and Turnover Intention.” Asia‐Pacific Journal of Management Research and Innovation 16, no. 3: 210–228. [Google Scholar]
  17. Fasbender, U. , Van der Heijden B. I., and Grimshaw S.. 2019. “Job Satisfaction, Job Stress and Nurses' Turnover Intentions: The Moderating Roles of On‐The‐Job and Off‐The‐Job Embeddedness.” Journal of Advanced Nursing 75, no. 2: 327–337. [DOI] [PubMed] [Google Scholar]
  18. Griffiths, P. , Ball J., Drennan J., et al. 2016. “Nurse Staffing and Patient Outcomes: Strengths and Limitations of the Evidence to Inform Policy and Practice. A Review and Discussion Paper Based on Evidence Reviewed for the National Institute for Health and Care Excellence Safe Staffing Guideline Development.” International Journal of Nursing Studies 63: 213–225. [DOI] [PubMed] [Google Scholar]
  19. Griffiths, P. , Maruotti A., Saucedo A. R., et al. 2019. “Nurse Staffing, Nursing Assistants and Hospital Mortality: Retrospective Longitudinal Cohort Study.” BMJ Quality and Safety 28, no. 8: 609–617. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Griffiths, P. , Saville C., Ball J. E., et al. 2020. The Safer Nursing Care Tool as a Guide to Nurse Staffing Requirements on Hospital Wards: Observational and Modelling Study. Vol. 8, 1–162. Southampton, UK: NIHR Journals Library. [PubMed] [Google Scholar]
  21. Hämmig, O. 2018. “Explaining Burnout and the Intention to Leave the Profession Among Health Professionals–a Cross‐Sectional Study in a Hospital Setting in Switzerland.” BMC Health Services Research 18, no. 1: 1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Health Service Executive . 2023. Health Sector Employment Report. Dublin: HSE. https://www.hse.ie/eng/staff/resources/our‐workforce/workforce‐reporting/health‐services‐employment‐report‐june‐23.pdf. [Google Scholar]
  23. Labrague, L. J. , Al Sabei S., Al Rawajfah O., AbuAlRub R., and Burney I.. 2022. “Interprofessional Collaboration as a Mediator in the Relationship Between Nurse Work Environment, Patient Safety Outcomes and Job Satisfaction Among Nurses.” Journal of Nursing Management 30, no. 1: 268–278. [DOI] [PubMed] [Google Scholar]
  24. Lake, E. T. 2002. “Development of the Practice Environment Scale of the Nursing Work Index.” Research in Nursing & Health 25, no. 3: 176–188. [DOI] [PubMed] [Google Scholar]
  25. Lake, E. T. , and Friese C. R.. 2006. “Variations in Nursing Practice Environments: Relation to Staffing and Hospital Characteristics.” Nursing Research 55, no. 1: 1–9. [DOI] [PubMed] [Google Scholar]
  26. Leineweber, C. , Chungkham H. S., Lindqvist R., et al. 2016. “Nurses' Practice Environment and Satisfaction With Schedule Flexibility Is Related to Intention to Leave due to Dissatisfaction: A Multi‐Country, Multilevel Study.” International Journal of Nursing Studies 58: 47–58. [DOI] [PubMed] [Google Scholar]
  27. Leone, C. , Bruyneel L., Anderson J. E., et al. 2015. “Work Environment Issues and Intention‐To‐Leave in Portuguese Nurses: A Cross‐Sectional Study.” Health Policy 119, no. 12: 1584–1592. [DOI] [PubMed] [Google Scholar]
  28. Lo, W. Y. , Chien L. Y., Hwang F. M., Huang N., and Chiou S. T.. 2018. “From Job Stress to Intention to Leave Among Hospital Nurses: A Structural Equation Modelling Approach.” Journal of Advanced Nursing 74, no. 3: 677–688. [DOI] [PubMed] [Google Scholar]
  29. Maben, J. , and Bridges J.. 2020. “COVID‐19: Supporting Nurses' Psychological and Mental Health.” Journal of Clinical Nursing 29, no. 15–16: 2742–2750. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Muir, K. J. , Sloane D. M., Aiken L. H., Hovsepian V., and McHugh M. D.. 2023. “The Association of the Emergency Department Work Environment on Patient Care and Nurse Job Outcomes.” Journal of the American College of Emergency Physicians Open 4, no. 5: e13040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Needleman, J. , Buerhaus P. I., Stewart M., Zelevinsky K., and Mattke S.. 2011. “Nurse Staffing and Patient Care Costs in Acute Inpatient Nursing Units.” New England Journal of Medicine 364: 1037–1045.21410372 [Google Scholar]
  32. Paguio, J. T. , Yu D. S. F., and Su J. J.. 2020. “Systematic Review of Interventions to Improve Nurses' Work Environments.” Journal of Advanced Nursing 76, no. 10: 2471–2493. [DOI] [PubMed] [Google Scholar]
  33. Pirret, A. M. , Corkery M. C., Gilhooly A., Devoy K. L., and Strickland W.. 2024. “The Comparison of the Nursing Activities Score and TrendCare to Accurately Measure Critical Care Nursing Workload: A Prospective Observational Design.” Intensive & Critical Care Nursing 81: 103568. [DOI] [PubMed] [Google Scholar]
  34. Plummer, V. M. 2015. Equity Ratios, Patient Dependency and Nursing Resource Management. Saarbrucken, Germany: Lambert Academic Publishing. [Google Scholar]
  35. Pursio, K. , Kankkunen P., Sanner‐Stiehr E., and Kvist T.. 2021. “Professional Autonomy in Nursing: An Integrative Review.” Journal of Nursing Management 29, no. 6: 1565–1577. [DOI] [PubMed] [Google Scholar]
  36. Roche, M. A. , and Duffield C. M.. 2010. “A Comparison of the Nursing Practice Environment in Mental Health and Medical‐Surgical Settings.” Journal of Nursing Scholarship 42, no. 2: 195–206. [DOI] [PubMed] [Google Scholar]
  37. Sermeus, W. , Aiken L. H., Ball J., et al. 2022. “A Workplace Organisational Intervention to Improve Hospital Nurses' and Physicians' Mental Health: Study Protocol for the Magnet4Europe Wait List Cluster Randomised Controlled Trial.” BMJ Open 12, no. 7: e059159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Sermeus, W. , Aiken L. H., Van den Heede K., et al. 2011. “Nurse Forecasting in Europe (RN4CAST): Rationale, Design and Methodology.” BMC Nursing 10, no. 1: 1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Shekelle, P. G. 2013. “Nurse–Patient Ratios as a Patient Safety Strategy: A Systematic Review.” Annals of Internal Medicine 158: 404–409. [DOI] [PubMed] [Google Scholar]
  40. Shin, S. , Park J.‐H., and Bae S.‐H.. 2018. “Nurse Staffing and Nurse Outcomes: A Systematic Review and Meta‐Analysis.” Nursing Outlook 66, no. 3: 273–282. 10.1016/j.outlook.2017.12.002. [DOI] [PubMed] [Google Scholar]
  41. Twigg, D. , and Duffield C.. 2009. “A Review of Workload Measures: A Context for a New Staffing Methodology in Western Australia.” International Journal of Nursing Studies 46, no. 1: 132–140. [DOI] [PubMed] [Google Scholar]
  42. Twigg, D. , Duffield C., Bremner A., Rapley P., and Finn J.. 2012. “Impact of Skill Mix Variations on Patient Outcomes Following Implementation of Nursing Hours per Patient Day Staffing: A Retrospective Study.” Journal of Advanced Nursing 68, no. 12: 2710–2718. [DOI] [PubMed] [Google Scholar]
  43. Välimäki, M. , Hu S., Lantta T., et al. 2024. “The Impact of Evidence‐Based Nursing Leadership in Healthcare Settings: A Mixed Methods Systematic Review.” BMC Nursing 23, no. 1: 452. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Van den Heede, K. , Cornelis J., Bouckaert N., Bruyneel L., Van de Voorde C., and Sermeus W.. 2020. “Safe Nurse Staffing Policies for Hospitals in England, Ireland, California, Victoria and Queensland: A Discussion Paper.” Health Policy 124, no. 10: 1064–1073. [DOI] [PubMed] [Google Scholar]
  45. Williams, D. , and Thomas S.. 2017. “The Impact of Austerity on the Health Workforce and the Achievement of Human Resources for Health Policies in Ireland (2008–2014).” Human Resources for Health 15, no. 1: 1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Wynendaele, H. , Willems R., and Trybou J.. 2019. “Systematic Review: Association Between the Patient–Nurse Ratio and Nurse Outcomes in Acute Care Hospitals.” Journal of Nursing Management 27, no. 5: 896–917. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1.

JAN-81-5973-s001.docx (197KB, docx)

Data S2.

JAN-81-5973-s002.docx (20.7KB, docx)

Data Availability Statement

Author elects to not share data.

Articles from Journal of Advanced Nursing are provided here courtesy of Wiley

RESOURCES