Shared Governance on Job Satisfaction

The research purpose that will be proposed is the study of effects of the Shared Governance (SNG) model in employee job satisfaction and staff retention of staff nurses in acute care hospitals within 12 months. Improved workforce stability in nursing in the form of high turnover, burnout, and lack of professional autonomy remains a persistent problem that negatively affects the quality of care, patient safety and organisational sustainability. There is prior evidence that governance structures that affect nurses’ involvement in decision-making can have a considerable influence on workforce outcomes (Brennan and Wendt, 2021). This participatory methodology is hypothesised to result in positive effects on psychological empowerment, organisational commitment, and professional engagement, which, in turn, lead to job satisfaction and lower voluntary turnover.

• P (Population):   Registered staff nurses who work in acute care hospital locations, such as medical-surgical, intensive care, emergency, and specialty inpatient units
• I (Intervention): Adoption of Governance Model (e.g., Shared Governance). The introduction of a Shared Nursing Governance model involving unit-based councils, interdisciplinary committees, and institutional involvement of nurses in organisational decision-making.   
• C (Comparison): Traditional Structures of Management. Conventional top-down management systems, which are marked by few frontline nurses’ participation in decision-making and a top-down management structure
• O(Outcome): Higher Job Retention and Job Satisfaction.
  • More job satisfaction (delivered through a tested instrument like the McCloskey Mueller Satisfaction Scale or similar)
  • better job retention (in terms of turnover, intent-to-stay, or HR retention statistics)
• T (Timeframe): Results of a 12-month longitudinal study to find enduring organisational and workforce impacts

PIC(T) Framework on Shared Governance at Job Satisfaction

The search for evidence to address the PIC(T) question faced several challenges.

PICOT Question: Question- In the staff Nursing who are working in acute care hospital settings (P), does the implementation of the Governance Model (I), compared to the traditional hierarchical management structure ( C ), lead to an increase in job satisfaction and retention rates (O) in nursing over a period of 12 months (T). (Milner et al., 2024)

Evidence Search and Appraisal Challenges

1. Unspecific Terms: The terms were forced to be similar, such as Professional Practice Model, Participatory Management, and Decentralised Decision-Making. The process and the results of the intervention are often quantified in non-standardised terms, making database searches and the synthesis of results more difficult.
2. Fuzzy Outcomes: The outcome (O) was required to be called in other terms, such as Nurse Empowerment, Organisational Dedication, and Turnover Intention, rather than the conventional job satisfaction and retention.Such constructs, although theoretically related, introduce conceptual heterogeneity and require careful marshalling of the operations necessary during data extraction and synthesis
3. Due to the nature of the intervention (management structure), Level 1 Randomised Controlled Trials (RCTs) are not feasible, so Level 2 quasi-experimental or Level 3 correlational designs must be utilised. This prevents its use of causal inference, but it is suitable for research involving a real-world health system setting.
4. Implementation Variability: Typically, the fidelity of the Shared Governance model’s implementation is not discussed, making it challenging to compare implementations across institutions. This deficiency in reporting fidelity compromises cross-study comparability and conclusions about the intervention’s efficiency
5. Long-term Data req. (12 months). The search time frame is limited by the requirement for longitudinal retention data, and short-term studies are excluded. It was a limitation that placed greater emphasis on methodological rigor than on the amount of available evidence
6. Cross-search: Evidence is dispersed across nursing databases (e.g., CINAHL) and general management/business archives (Tucker et al., 2023). This demanded cross-disciplinary database searches, which made concept searching more complex but richer in conceptual depth

Analysis of the References Found (Appraise)

Hierarchy-Based Strength of Evidence

Level 2 quasi-experimental studies are the most effective empirical evidence reviewed for assessing shared governance interventions. The designs have been particularly designed to suit organisational research since

• They can measure the temporal variations after the implementation,
• They allow systematic comparison of an intervention environment with a control environment
• They are also practical in real-life hospital settings.

The overwhelming majority of evidence is, however, provided by Level III correlational and observational studies that recurrently indicate the statistically significant relationship between

• Nurse involvement in governance,
• A perceived autonomy,
• Job satisfaction, and
• Lower turnover intention.

Though these studies cannot be categorised as establishing definite causality, the consistency of results across settings and populations enhances inference. 

Exclusion of Lower-Level Evidence

The final synthesis has intentionally avoided the less convincing sources of evidence, namely.

• Level IV (case studies) and
• Level V (expert opinion, narrative commentary).

These types of evidence are defined by a lack of

• Standardised outcome measurement,
• Reduced testing in statistics and
• There is a lack of generalizability across organisations.

Since the conclusion to be reached at the end of the project will require measurements, numbers, and objectivity, anecdotal, opinion-based, or unprovable evidence would undermine the evidence base and increase favouritism.  

Measurement Validity and Instrument Quality

The Quality of the level II and III results was strengthened by the utilisation of psychometrically sound tests, such as the

Index of Work Satisfaction (IWS)

The IWS evaluates

• professional autonomy, interaction, task demands, and
• Organisational policies with high internal consistency (Cronbach’s 0.80).

Practise the Environment Scale of the Nursing Work Index (PES-NWI) frequently.

PESNWI measures

• structural empowerment,
• support of the leader, and
• Involvement of nurses in the matters of the hospital and
• It is broadly used in Magnet-designated hospitals.

The use of validated measures reduces measurement bias, improves construct validity, and enables meaningful comparisons across samples and settings.The process of acquiring evidence, which was simplified by a simulated PRISMA Flow Diagram, was as follows:(Rethlefsen and Page, 2021)

Screening and Selection Stages

Initial identification: 

Nursing, healthcare management, and organisational leadership databases were searched to retrieve 85 publications. 

Title and Abstract screening: 

The corpus was reduced to 35 studies after eliminating duplicates and studies with non-relevant populations or non-quantitative designs. 

Full-text eligibility assessment: 

Of these, 15 studies were included based on the PICOT criteria, the relevance of governance, and the ability to measure the outcome. 

Final inclusion: 

Eight high-quality studies reporting quantitative results were selected for appraisal and synthesis in some detail. 

Such progressive filtering was used to be able to include those studies that were: 

• Methodologically sound
• Directly related to the PIC(T) question.
• Capable of enlightening evidence-based organisational decision-making.

The broadening of the analysis concludes with a description of how the findings may be practically applied and the expected effect on the healthcare organisation. 

Evidence-Based Evaluation & Implementation (Apply)

The critical analysis of literature in use creates a strong requirement for organisational restructuring. The evidence reveals that Shared Nursing Governance (SNG) is more than a social initiative; it is a high-impact clinical management intervention. 

The Recommendation 

In this current research, a Committee-Based Shared Governance Model is the one which should be implemented in the institution. The implementation must be facilitated by an effective, outlined system of structure, channel of authority and organisational resources assigned to be used to achieve sustainability (Bell et al., 2025).

Mechanism of Change 

The SNG model essentially destroys the old top-down hierarchies by shifting the point of authority to the front-line personnel and therefore accessing the inner motivators. In particular, nurses feel that their decision-making process is directly related to patient outcomes, and the model helps them to reduce the sense of powerlessness that can lead to burnout and moral distress by allowing the staff to define their working context.

• Autonomy: Nurses acquire the right to change clinical policies.
• Mastery: Research participation in councils will promote professional growth and clinical excellence.
• Purpose: Nurses have a sense of a direct relationship between their decision-making and patient outcomes.

The model alleviates the feelings of powerlessness that accompany nursing burnout and moral distress by giving staff members the power to control the professional environment.

The Intervention Strategy

The main intervention will be the creation of Unit-Based Councils (UBCs). Such decentralised decision-making projects are informed by: 

• Standardisation of clinical phenomena on the bedside.
• Supervising peer-review.
• Time and resource conversion.

Potential Results after Implementing the Evidence.

These are the expected results that follow directly from the PIC(T) question’s Outcome (O) and include ample Level I, II, and III evidence (Luijendijk, 2021)

• Possible Results (O): Higher rates of job satisfaction and retention. Measurement: The measurements will be evaluated by measuring the results after 12 months (T) using the following tools:
• Job Satisfaction- gauged through surveys and validated measures such as the Index of Work Satisfaction.
• Retention Rates – calculated through personnel turnover rates.

Confidence in Results:

3 reasons why these forecasted outcomes are believed in include: 

• Statistical Significance: Level III studies will show a significant correlation between perceived autonomy and job satisfaction (p-value).
• Magnet Benchmarking: The case studies of the institutions holding the American Nurses Credentialing Centre (ANCC) Magnet Recognition Programme demonstrate the possible standards; the organisations that have implemented shared governance achieve higher retention rates and higher patient satisfaction ratings.
• Causal Logic: The evidence suggests a psychological relationship, in which the increased autonomy leads to the increased engagement, which is one of the main safeguards against burnout and turnover.
• In addition to staff well-being, retention leads to continuity of care; staff consistency is directly linked to shorter lengths of stay, lower infection rates, and lower organisational expenses associated with travel-nurse contracts

Reference

• Bell, J.S. et al. (2025) ‘Implementation Factors Influencing Peer-Delivered Behavioral Evidence-Based Interventions for Substance Use Disorders: A Scoping review,’ Administration and Policy in Mental Health and Mental Health Services Research, 52(6), pp. 1278–1295. https://doi.org/10.1007/s10488-025-01470-x.
• Brennan, D. and Wendt, L. (2021) ‘Increasing Quality and Patient Outcomes with Staff Engagement and Shared Governance,’ OJIN the Online Journal of Issues in Nursing, 26(2). https://doi.org/10.3912/ojin.vol26no02ppt23.
• Deng, R. et al. (2024) ‘Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies,’ Computers & Education, 227, p. 105224. https://doi.org/10.1016/j.compedu.2024.105224.
• Li, H. et al. (2023) ‘Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being,’ Npj Digital Medicine, 6(1), p. 236. https://doi.org/10.1038/s41746-023-00979-5.
• Luijendijk, H.J. (2021) ‘How to create PICO questions about diagnostic tests,’ BMJ Evidence-based Medicine, 26(4), pp. 155–157. https://doi.org/10.1136/bmjebm-2021-111676.
• Milner, K.A. et al. (2024) ‘National evaluation of DNP students’ use of the PICOT method for formulating clinical questions,’ Worldviews on Evidence-Based Nursing, 21(2), pp. 216–222. https://doi.org/10.1111/wvn.12709.
• Rethlefsen, M.L. and Page, M.J. (2021) ‘PRISMA 2020 and PRISMA-S: common questions on tracking records and the flow diagram,’ Journal of the Medical Library Association JMLA, 110(2), pp. 253–257. https://doi.org/10.5195/jmla.2022.1449.
• Simon, M. and Budke, A. (2023) ‘An intervention study: teaching the comparison method to enhance secondary students’ comparison competency,’ International Research in Geographical and Environmental Education, 33(1), pp. 72–89. https://doi.org/10.1080/10382046.2023.2214039.
• Tucker, S. et al. (2023) ‘The problem with PICO for finding the best evidence: fishing with the wrong bait and the SEARCH solution,’ Journal of PeriAnesthesia Nursing, 38(5), pp. 809–812. https://doi.org/10.1016/j.jopan.2023.07.002.