critical appraisal nursing research

Critical Appraisal Resources for Evidence-Based Nursing Practice

What is critical appraisal, critical appraisal tools, video: learn more about the joanna briggs institute.

Levels of Evidence
Systematic Reviews
Randomized Controlled Trials
Quasi-Experimental Studies
Case-Control Studies
Cohort Studies
Analytical Cross-Sectional Studies
Qualitative Research

Recommended Books on Critical Appraisal

Critical appraisal is an essential and important step in the evidence-based practice (EBP) process. It involves analyzing and critiquing the methodology and data of published research studies (both quantitative and qualitative designs) to determine the value, reliability, trustworthiness, and relevance of those studies in answering a clinical question.

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Critical Appraisal

Use this guide to find information resources about critical appraisal including checklists, books and journal articles.

Key Resources

This online resource explains the sections commonly used in research articles. Understanding how research articles are organised can make reading and evaluating them easier View page
Critical appraisal checklists
Worksheets for appraising systematic reviews, diagnostics, prognostics and RCTs. View page
A free online resource for both healthcare staff and patients; four modules of 30–45 minutes provide an introduction to evidence based medicine, clinical trials and Cochrane Evidence. View page
This tool will guide you through a series of questions to help you to review and interpret a published health research paper. View page
The PRISMA flow diagram depicts the flow of information through the different phases of a literature review. It maps out the number of records identified, included and excluded, and the reasons for exclusions. View page
A useful resource for methods and evidence in applied social science. View page
A comprehensive database of reporting guidelines. Covers all the main study types. View page
A tool to assess the methodological quality of systematic reviews. View page

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Chapter 5 covers critical appraisal of the literature. View this eBook

Chapter 6 covers assessing the evidence base. Borrow from RCN Library services

Section 1 covers an introduction to critical appraisal. Section 3 covers appraising difference types of papers including qualitative papers and observational studies. View this eBook

Chapter 6 covers critically appraising the literature. Borrow from RCN Library services

View this eBook

Chapter 8 covers critical appraisal of the evidence. View this eBook

Chapter 18 covers critical appraisal of nursing studies. View this eBook

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Critical appraisal

Journal articles

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Shea BJ and others (2017) AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions or both, British Medical Journal, 358.

An outline of AMSTAR 2 and its use for as a critical appraisal tool for systematic reviews. View article (open access)
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Postgraduate Nursing: Critical appraisal and Evaluation of research

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Introduction to critical appraisal and evaluation

The information you use in your research and study must all be credible, reliable and relevant. Part of the Evidence-Based Practice process is to critically appraise scientific papers, but in general, all the resources you refer to should be evaluated carefully to ensure their credibility.

How can you tell whether the resources you've found are credible and suitable for you to reference? To evaluate Information you have found on websites, see the video below and the box on using Internet sites. Journal articles and academic texts should at least have gone through a process of peer review (see the video about peer review on the Journals page of this guide).

Critical appraisal of scientific papers takes the evaluation to another level. Once you have asked the clinical question and searched for evidence, it's often not enough that you've checked for peer review if you want to find the very best evidence - it will ensure that studies with scientific flaws are disregarded, and the ones you include are relevant to your question.

In the Evidence-Based Practice process, and especially in the process of evaluating primary research (which hasn't be pre-appraised or filtered by others), we need to go beyond the usual general information evaluation and make sure the evidence we are using is scientifically rigorous. The main questions to address are:

Is the study relevant to your clinical question?
How well (scientifically) was the study done, especially taking care to eliminate bias?
What do the results mean and are they statistically valid (and not just due to chance)?

For a more detailed look at Critical Appraisal, head to the Systematic Review Guide - Critical Appraisal and the Evidence-Based Practic Guide - Appraise.

Critical appraisal tools

Fortunately, there have been some great checklist tools developed for different types of studies. Here are some examples:

The Joanna Briggs Institute (JBI) provides access to critical appraisal tools, a collection of checklists that you can use to help you appraise or evaluate research.
Critical Appraisal Skills Programme (CASP) is part of Better Value Healthcare based in Oxford, UK. It includes a series of checklists , suitable for different types of studies and designed to be used when reading research.
The Equator Network is devoted to Enhancing the QUAlity and Transparency Of health Research. Among other functions, they include a Toolkit for Peer Reviewing Health Research which is very useful as a guide for critically appraising studies.
Critical Appraisal Tools (CEBM) - This site from the Centre of Evidence Based Medicine includes tools and worksheets for the critical appraisal of different types of medical evidence.
Critical Appraisal Tools (iCAHE) - This site from the International Centre of Allied Health Evidence (at the University of South Australia) has a range of tools for various types of studies.
Understanding Health Research - is from the Medical Research Council in the UK. It's a very handy all-purpose tool which takes you through a series of questions about a particular article, highlighting the good points and possible problem areas. You can print off a summary at the end of your checklist

Critical appraisal tools from the NHS in Scotland links interactively to all sorts of resources on how to identify the study type and build your critical appraisal skills, as well as to tools themselves.

Critical reading and understanding research

A useful series of articles for nurses about critiquing and understanding types of research has been published in the Australian Journal of Advanced Nursing by Rebecca Ingham-Broomfield, from the University of New South Wales:

Ingham-Broomfield, R. (2014). A nurses' guide to the critical reading of research . Australian Journal of Advanced Nursing , 32 (1), 37-44. [Updated from 2008.]

Ingham-Broomfield, R. (2014). A nurses' guide to quantitative research . Australian Journal of Advanced Nursing, 32 (2), 32-38.

Ingham-Broomfield, R. (2015). A nurses' guide to qualitative research . Australian Journal of Advanced Nursing, 32 (3), 34-40.

Ingham-Broomfield, R. (2016). A nurses' guide to mixed methods research . Australian Journal of Advanced Nursing, 33 (4), 46-52.

Ingham-Broomfield, R. (2016). A nurses' guide to the hierarchy of research designs and evidence . The Australian Journal of Advanced Nursing, 33 (3), 38-43.

Evaluate internet resources

The website domain gives you an idea of the reliability of a website:

Critical appraisal resources

Introduction to Critical Appraisal - This short video from the library at the University of Sheffield in the UK looks at the background to critical appraisal, what it is, and why we do it. A very useful introduction to the topic.

Evaluating information

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Nursing Research: Methods and Critical Appraisal for Evidence-Based Practice

Geri LoBiondo-Wood Geri LoBiondo-Wood Search for articles by this author
Judith Haber Judith Haber Search for articles by this author

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DOI: https://doi.org/10.1016/S2155-8256(15)30102-2

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Course Descriptions

Prereq: Admission to the BSNa Option Program
Prereq: Admission to the Nursing major
Prereq: Enrollment in BSN traditional program; or enrollment in aBSN program; or permission of instructor.
Prereq: Nursing 2451, and enrollment in BSN traditional program; or enrollment in aBSN program; or permission of instructor.
Prereq: Enrollment in the BSN traditional program; or enrollment in aBSN program.
Prereq: 1100 or 5115; and 2200, 2201, 2271, 2272, 2451, 2452, 2500, and 2782; and Micrbio 4000; and HumnNtr 2210, 2310, or 2410; and enrollment in BSN traditional program; or permission of instructor.
Prereq: Enrollment in the BSNa option program.
Prereq: 3275, and enrollment in the BSNa option program.
Prereq: Enrollment in the Nursing major. Not open to students with credit for 440.
Prereq: 2270, 3270, and 4260; or enrollment in the aBSN program.
Prereq: 3240, 3260, 3271, 3272, 3280, 3460, and 3780 and enrollment in the BSN traditional program or permission of instructor.
Prereq: 3240, 3260, 3271, 3272, 3280, 3460, and 3780 and enrollment in the BSN traditional program or permission of instructor
Prereq: 3240, 3260, 3271, 3272, 3280, 3460, 3780, and enrollment in the BSN traditional program or permission of instructor
Prereq: 3276, 4240s, 4341, and enrollment in the BSNa option program
N5115:MINDSTRONG: An Evidence-based Program to Reduce Stress and Promote Overall Well-being-Through a series of educational and skills building activities, this course provides an evidence-based program that reduces stress, improves mental resiliency and builds protective factors that improve overall health, well-being, and academic performance. This course is graded S/U.

Teaching critical appraisal skills for nursing research

Affiliation.

1 Centre for Health Initiatives, University of Wollongong, Room 41.G04, University of Wollongong, Wollongong, NSW 2522, Australia. [email protected]
PMID: 21474381
DOI: 10.1016/j.nepr.2011.03.002

Background: Evidence-based practice is a major focus in nursing, yet the literature continues to document a research-practice gap. Reasons for this gap stem partly from a lack of skills to critique and synthesize the literature, a lack of search skills and difficulty in understanding research articles, and limited knowledge of research by nursing professionals.

Method: An innovative and quality driven subject to improve critical appraisal and critical thinking skills was developed for the School of Nursing, Midwifery and Indigenous Health at the University of Wollongong, based on formative research with postgraduate students and supervisors. Through face-to-face and online teaching modules students worked through a structured process of analysing the key aspects of published papers using structured analysis tools for each study design.

Results: Pre and post surveys of students found improvements in perceived knowledge of all key skills of critical appraisal. External independent evaluation determined that it was a high quality subject showing many hallmarks of good assessment practice and good practice in use of information and communication technology (ICT) in support of the learning outcomes.

Evidence-Based Nursing / education*
Nursing Education Research
Nursing Research / education*
Schools, Nursing

Open access
Published: 13 May 2024

From incivility to outcomes: tracing the effects of nursing incivility on nurse well-being, patient engagement, and health outcomes

Nourah Alsadaan ORCID: orcid.org/0000-0001-7285-0184 1 ,
Osama Mohamed Elsayed Ramadan ORCID: orcid.org/0000-0002-9616-8590 1 &
Mohammed Alqahtani 2

BMC Nursing volume 23 , Article number: 325 ( 2024 ) Cite this article

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Nursing incivility, defined as disrespectful behaviour toward nurses, is increasingly recognized as a pressing issue that affects nurses’ well-being and quality of care. However, research on the pathways linking incivility to outcomes is limited, especially in Saudi hospitals. Methods: This cross-sectional study examined relationships between perceived nursing incivility, nurse stress, patient engagement, and health outcomes in four Saudi hospitals. Using validated scales, 289 nurses and 512 patients completed surveys on exposure to incivility, stress levels, activation, and medication adherence. The outcomes included readmissions at 30 days and satisfaction. Results: More than two-thirds of nurses reported experiencing moderate to severe workplace incivility. Correlation and regression analyzes revealed that nursing incivility was positively associated with nursing stress. An inverse relationship was found between stress and patient participation. Serial mediation analysis illuminated a detrimental cascade, incivility contributing to increased nurse stress, subsequently diminishing patient engagement, ultimately worsening care quality. Conclusions The findings present robust evidence that nursing incivility has adverse ripple effects, directly impacting nurse well-being while indirectly affecting patient outcomes through reduced care involvement. Practical implications advocate for systemic interventions focused on constructive nursing cultures and patient empowerment to improve both healthcare provider conditions and quality of care. This study provides compelling information to inform policies and strategies to mitigate workplace mistreatment and encourage participation among nurses and patients to improve health outcomes.

Peer Review reports

Introduction

Nursing, a cornerstone of the healthcare system, plays an indispensable role in patient care and the broader health landscape [ 1 , 2 ]. This noble profession encompasses not only the administration of treatments and medications but also the provision of emotional support and education to patients and their families [ 3 , 4 ]. Nurses are often the primary point of contact for patients, which makes their role crucial in shaping patient experiences and outcomes [ 5 ]. The diverse responsibilities, from bedside care to patient advocacy, emphasize the multifaceted nature of nursing and its critical impact on the delivery of healthcare [ 6 , 7 ]. The work environment in which nurses work is crucial for both their well-being and their ability to provide quality care [ 6 , 8 ]. A positive and supportive environment not only improves job satisfaction and retention among nurses but also directly influences patient safety and quality of care [ 9 , 10 ]. Factors such as teamwork, communication, and organizational culture play an important role in shaping this environment [ 11 ]. In contrast, negative elements within the workplace can lead to burnout, decreased job satisfaction, and potentially compromise patient care [ 12 ].

Nursing incivility, an increasingly distressing concern, encompasses disrespectful behaviours [ 13 ], that violate workplace dignity norms ranging from subtle belittling to overt hostility [ 2 , 8 ]. This widespread phenomenon permeates most healthcare settings [ 14 , 15 ], with up to 85% of nurses encountering this mistreatment from various sources [ 16 ], resulting in a significantly disruptive organizational climate [ 17 ]. Beyond affecting nurse well-being through adverse psychological impacts, incivility breeds poor morale, compromised performance, increased attrition, and, critically, reduced quality of patient care [ 18 , 19 , 20 ]. Prioritizing healthy collegial environments remains crucial for upholding both nurse wellness and optimal patient outcomes [ 21 , 22 , 23 ]. Furthermore, organizational factors, such as leadership, communication, and workplace culture, may play a significant role in shaping the dynamics of nursing incivility, stress, and patient outcomes [ 24 , 25 ]. Investigating these factors could provide a more comprehensive understanding of the complex interplay between individual and systemic elements in the healthcare setting [ 26 , 27 ]. Nursing incivility can manifest itself in various forms, including, but not limited to, belittling comments, bullying, gossip, and exclusionary tactics [ 11 , 28 ]. These behaviours can originate from colleagues, superiors, patients, and their families [ 16 , 29 ]. Such conduct not only undermines professional relationships [ 30 ] but also can cause psychological distress for victims, preventing their ability to perform effectively [ 31 , 32 ].

Although the prevalence and nature of incivility in nursing have been well documented, there remains a significant gap in understanding its full impact [ 33 , 34 ]. The impact of nursing incivility extends beyond the immediate targets, affecting multiple aspects of healthcare delivery [ 35 , 36 ]. Incivility can have profound emotional consequences for nurses, leading to increased stress, burnout, and job dissatisfaction, which can compromise their ability to provide high-quality patient care [ 8 , 19 , 29 ]. Moreover, uncivil behaviors can strain nurse-patient interactions, potentially diminishing the quality of care and patient satisfaction [ 18 , 37 ]. At an organizational level, incivility can disrupt team dynamics, contribute to higher staff turnover rates, and negatively influence the overall culture within healthcare institutions [ 18 , 38 , 39 ]. Furthermore, the economic implications of nursing incivility, such as costs associated with staff replacement and lost productivity due to absenteeism and presenteeism, warrant further investigation [ 40 , 41 , 42 ]. Examining these multifaceted impacts is crucial for developing targeted interventions and policies to mitigate the detrimental effects of incivility on nurses, patients, and healthcare organizations [ 43 , 44 ].

Current literature has primarily focused on identifying forms and instances of uncivil behavior, often overlooking their deeper implications for nurses, patients, and healthcare systems. An underexplored area is the direct effect of incivility on nurses’ well-being [ 8 ]. This includes quantifying the emotional and professional toll, such as stress, burnout, and job dissatisfaction [ 31 ], which are crucial factors influencing nurse retention and mental health [ 45 , 46 ].

In summary, filling these gaps through robust empirical research is crucial. Such research is essential not only to transform current anecdotal and observational understandings into data-driven insights but also to develop effective strategies to mitigate the negative impacts of incivility [ 47 , 48 ]. These insights are vital to promoting a healthier, more respectful, and efficient healthcare environment, ultimately enhancing nurses’ well-being and patient care quality [ 3 , 5 ]. The primary objective of this study was to investigate the impact of nursing incivility on critical aspects of healthcare care delivery. By focusing on nurse stress, patient engagement, and health outcomes (defined as 30-day readmission rates and patient satisfaction scores), the study aimed to understand how incivility in the nursing environment affects both healthcare providers and recipients.

The study was conducted within the context of the Saudi healthcare system, which has undergone significant reforms in recent years [ 49 , 50 ]. The system is primarily government-funded, with a growing private-sector presence [ 51 ]. It aims to provide universal access to healthcare services for all citizens and residents, with a focus on improving quality and efficiency [ 52 ]. However, like many healthcare systems worldwide [ 53 , 54 ], it faces challenges related to workforce development, patient satisfaction, and the management of complex health conditions [ 55 ]. Understanding the impact of nursing incivility within this context is crucial for informing strategies to enhance the well-being of healthcare providers and the quality of patient care.

This study examined nurse stress, a direct consequence of incivility, and its subsequent effects on patient care. Additionally, it explored how incivility in nursing influenced patient participation, a crucial factor in successful health outcomes. Finally, the study assessed the broader implications of these variables on overall health outcomes, providing valuable insights for healthcare policy and practice.

This study’s findings can influence nursing practice and patient care significantly. By demonstrating the tangible impacts of nursing incivility, the study can inform the development of targeted interventions and policies to create a more respectful and supportive work environment for nurses. This, in turn, can lead to improved patient care and outcomes. Highlighting the importance of a respectful and supportive nursing environment is a key outcome of this study. By underscoring the detrimental effects of incivility, the research advocates for a cultural shift in healthcare settings toward more positive and collaborative interactions. These changes are vital for nurses’ well-being, patient care quality, and healthcare organizations’ overall effectiveness.

Materials and methods

Research objectives & research hypothesis.

Examine the relationships between nursing incivility, nurse stress (defined as emotional exhaustion and depersonalization), patient engagement (defined by patient activation levels and adherence to discharge protocols), and health outcomes (defined as 30-day readmission rates and patient satisfaction scores). H1a: Higher levels of nursing incivility will be positively associated with increased nurse stress. H1b: Higher levels of nurse stress will be negatively associated with patient engagement. H1c: Lower levels of patient engagement will be associated with poorer health outcomes.

Investigate how different perceived levels and types of nursing incivility, including overt (bullying, verbal abuse) and covert (gossip, exclusion) behaviours frequently reported by nurses, affect nurse stress and emotional exhaustion through a cross-sectional survey methodology.

H2a: Overt forms of nursing incivility will have a stronger positive association with nurse stress compared to covert forms of incivility. Overt forms of nursing incivility refer to more explicit and direct forms of uncivil behaviour, such as verbal abuse, bullying, or intimidation. Covert forms of nursing incivility refer to more subtle and indirect forms of uncivil behaviour, such as gossip, exclusion, or undermining actions.

H2b: A higher frequency of exposure to nursing incivility will be associated with higher levels of nurse stress and emotional exhaustion.

Evaluate how nursing incivility, nurse stress, and patient engagement (activation and adherence) impact patient health outcomes (30-day readmissions and satisfaction), mapping the relationships between these variables using multivariate regression techniques. H3a: Nursing incivility will have a direct negative effect on patient health outcomes. H3b: Nurse stress will mediate the relationship between nursing incivility and patient health outcomes. H3c: Patient engagement will mediate the relationship between nurse stress and patient health outcomes. H3d: The combined indirect effects of nurse stress and patient engagement will partially mediate the relationship between nursing incivility and patient health outcomes.

These hypothesized relationships form the conceptual foundation of our study, guiding our investigation into the complex interplay between nursing incivility, nurse well-being, patient engagement, and healthcare outcomes. By examining these relationships, we aim to provide insights into the potential cascading effects of uncivil behaviours in the nursing workplace and their ultimate impact on patient care. Figure 1 illustrates the hypothesized relationships between nursing incivility, nurse stress, patient engagement, and health outcomes. As depicted in Fig. 1 , we hypothesize that nursing incivility directly influences nurse stress and patient engagement. In turn, nurse stress is expected to have an indirect effect on health outcomes, mediated by patient engagement. Additionally, we anticipate that patient engagement directly impacts health outcomes, which are operationalized as readmission rates and patient satisfaction.

The arrows in Fig. 1 are used to represent the relationships and directional hypotheses between the constructs mentioned: Nursing Incivility, Nurse Stress, Patient Engagement, and Health Outcomes. Here’s how the arrows correspond to each hypothesis:

Solid Arrows indicate a direct relationship in the primary sequence of effects :

H1a: Nursing Incivility → Nurse Stress.

H1b: Nurse Stress → Patient Engagement.

H1c: Patient Engagement → Health Outcomes

Dashed Arrows represent different types of incivility (overt and covert) and their effect on Nurse Stress :

H2a: Nursing Incivility (Overt) → Nurse Stress.

H2b: Nursing Incivility (Covert) → Nurse Stress.

Dotted Arrows show both direct and mediated paths for complex relationships :

H3a: Direct effect from Nursing Incivility → Health Outcomes.

H3b: Mediated effect through Nurse Stress.

H3c: Mediated effect through Patient Engagement.

H3d: Combined mediation through Nurse Stress and Patient Engagement leading to Health Outcomes.

Hypothesized relationships between nursing incivility, nurse stress, patient engagement, and health outcomes

This study employed a cross-sectional correlational design to explore the relationships between nursing incivility, nurse stress, patient engagement, and health outcomes. This design involved collecting data from a defined population of nurses and patients in acute care settings simultaneously. This approach allows us to examine the associations between variables without actively manipulating any of them, providing a snapshot of the current state of these relationships.

The study was conducted in four hospitals located in the northwest region of Saudi Arabia. The participating hospitals are large, general medical and surgical facilities, with bed capacities ranging from 200 to 500. They provide a wide range of services, including inpatient and outpatient care, emergency services, critical care units, and specialized departments such as maternity, paediatrics, and mental health treatment. The patient population served by these hospitals is diverse, encompassing individuals seeking acute care for various medical conditions as well as those managing chronic illnesses such as diabetes, cardiovascular diseases, and respiratory disorders. The hospitals cater to both urban and rural communities within the northwest region. The nursing staff in these hospitals comprises a combination of Saudi and expatriate nurses, with varying levels of experience and educational qualifications. It is important to note that the findings of this study are specifically relevant to the northwest region of Saudi Arabia and may not be generalizable to other regions or healthcare settings. The unique cultural and socioeconomic characteristics of this region should be considered when interpreting the results and their implications for nursing practice and patient care.

Participant sample size determination

We calculated sample sizes for the nurse and patient groups to ensure statistical validity and practicality in our cross-sectional study. For the 289 nurses, we conducted a power analysis using a moderate effect size, 80% power, and a 0.05 alpha level, following the guidelines of Cohen (2013) on power analysis for behavioural sciences [ 56 ]. Although a small effect size might initially seem appropriate given the significant knowledge gap addressed by our study, the moderate effect size was chosen to maintain a balance between sensitivity and feasibility. This decision was particularly influenced by the practical challenges associated with securing a large enough sample to detect small effects within the logistical and resource constraints of our study setting. The moderate effect size was deemed most appropriate given the limited existing research on the specific relationships between nursing incivility, nurse stress, patient engagement, and health outcomes within the Saudi Arabian context, as highlighted in the introduction. Additionally, we accounted for potential variability and non-response rates for healthcare research, as suggested by Davern (2013).

The patient group required a larger sample size of 512 to accommodate greater variability and enable subgroup analyses. Patients were selected using a combination of random sampling and voluntary participation. Initially, a random sample of patients was drawn from the patient records of the participating hospitals, ensuring a representative mix of demographics, diagnoses, and hospital units. These patients were then invited to participate in the study voluntarily, which aimed to minimize selection bias while ensuring patient autonomy.

This approach also adhered to the standard power analysis methods [ 56 ] and included an upward adjustment for expected variability in patient responses, as recommended by Hulley et al. (2013) in their guidelines for clinical research [ 57 ]. Both sample sizes were further validated for feasibility within our resource constraints and specific healthcare settings, aligning with the practical considerations outlined by [ 58 ] in planning health research. In summary, the sample sizes of 289 nurses and 512 patients were determined using established statistical methods and customized to the unique aspects of our study, ensuring adequate power for reliable results. The selection process for both nurses and patients aimed to balance representativeness, statistical power, and ethical considerations, with patient selection particularly focused on combining random sampling with voluntary participation.

Eligibility criteria

Inclusion criteria.

Participants selected for this study were required to meet several conditions. First, they had to be registered nurses actively employed full-time, working ≥ 30 h per week, at one of the four identified healthcare hospitals. Their experience in the current institution should have spanned a minimum of six months. Furthermore, only those who could and were willing to provide informed consent were considered. Language proficiency was also crucial; Participants had to be fluent in Arabic or English to ensure they understood and completed the survey accurately. Lastly, the age bracket for eligible nurses was established between 25 and 60 years. Additionally, eligible participants must participate in direct patient care activities at least 10 h per week.

Exclusion criteria

Several factors led to the exclusion of potential participants from this study. Nurses who were currently not in active service, perhaps due to long-term leave or sabbatical, were not considered. We also considered the health aspect; nurses who self-declared cognitive impairments or mental health problems that could influence the accuracy of their responses were excluded. Nurses who had participated in a similar study or survey related to the topic in the last 6 months were excluded from this research. This exclusion criterion was implemented to minimize the potential influence of recent exposure to similar research questions or interventions on participants’ responses. By ensuring that a sufficient washout period had passed since any previous participation in related studies, we aimed to reduce the risk of response bias and enhance the validity of the collected data. This criterion contributes to the study’s rigour by minimizing the potential confounding effects of prior research experiences and promoting the collection of more independent and unbiased responses from participants.

Data collection tools

In this study, we employed the following validated instruments to measure the key variables, aligning with our research objectives and hypotheses:

Nursing incivility scale (NIS)

The Nursing Incivility Scale (NIS) is a quantitative instrument comprising 43 items designed to measure the frequency of perceived incivility from various sources, including patients, supervisors, coworkers, and physicians, over the preceding six months [ 59 ]. The NIS includes subscales that assess various sources of incivility, such as from nurses, supervisors, physicians, and patients. The items within these subscales capture both overt and covert forms of incivility, allowing for an assessment of the frequency and severity of each type of uncivil behaviour [ 60 ].

It employs a 5-point Likert scale ranging from “Never” to “Daily” and encompasses five subscales addressing different sources of incivility: nurses, the general workplace, supervisors, physicians, and patients The Nursing Incivility Scale (NIS) doesn’t provide a direct score but rather collects data on the frequency of uncivil behaviours experienced by nurses [ 60 , 61 ]. The NIS has demonstrated excellent internal reliability (Cronbach’s α > 0.90 across subscales) [ 56 ], and validity, making it well-suited for exploring the correlation between nursing incivility and nurse stress. Higher scores on the NIS subscales indicate a higher frequency of exposure to various forms of incivility from different sources.

Perceived stress scale (PSS)

The Perceived Stress Scale (PSS) is a 10-item self-report questionnaire that evaluates an individual’s stress appraisal over the preceding month, with a particular emphasis on predictability, control, and overload [ 62 ]. It employs a 5-point Likert scale ranging from “Never” to “Very Often.” The total PSS score typically ranges from 0 to 40 (assuming a 4-point scale), with higher scores indicating greater perceived stress and emotional exhaustion. A common interpretation guide categorizes scores as follows: 0–13 for low stress, 14–26 for moderate stress, and 27–40 for high perceived stress. The PSS has been extensively validated, exhibiting good internal reliability (Cronbach’s α = 0.78), rendering it pertinent for assessing stress levels and emotional exhaustion among nurses [ 63 ].

Patient activation measure (PAM)

A 13-item scale measuring patient self-efficacy in managing their health and care [ 64 ]. The Patient Activation Measure (PAM) employs a 4-point Likert scale, ranging from “Strongly Disagree” (1) to “Strongly Agree” (4), to assess the level of patient involvement in their healthcare. The raw scores from each question are summed, and this raw score is then mathematically transformed to a 0-100 scale. The final PAM score reflects the degree of a patient’s activation, with a score range of 1–46 indicating low activation, wherein patients tend to be overwhelmed and unprepared to take an active role in their health; 47–55 suggesting moderate activation, where patients are somewhat comfortable managing their health but might require assistance; 56–72 signifying high activation, with patients being comfortable in taking an active role in managing their health; and 73–100 representing very high activation, wherein patients are highly confident and skilled in managing their health [ 65 ].

Morisky Medication Adherence Scale (MMAS-8)

The Morisky Medication Adherence Scale (MMAS-8) is a validated 8-item self-report instrument designed to identify barriers to medication adherence [ 66 ]. It employs a binary response format (yes/no) to assess adherence issues over the past week. The MMAS-8 exhibits good internal consistency (Cronbach’s α = 0.83) and reliability, rendering it a crucial tool for evaluating patient engagement concerning medication adherence. Patients are categorized into different adherence levels based on their cumulative score ranging from 0 to 8, with a score of 8 indicating high adherence (likely following medication instructions), scores of 6 or 7 suggesting medium adherence (potential for missed medications), and scores below 6 signifying low adherence (high risk of not following instructions) [ 67 ].

Hospital Consumer Assessment of Healthcare Providers and systems (HCAHPS)

The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) is a survey instrument and data collection methodology to measure patients’ perceptions of their hospital experience [ 68 ]. The survey contains 29 questions about the recent hospital stay of patients, including communication with nurses and doctors, hospital staff responsiveness, cleanliness and quietness of the hospital environment, communication about medications, discharge information, overall hospital rating, and whether they would recommend the hospital [ 69 ]. The survey is administered to a random sample of adult patients across medical conditions between 48 h and six weeks after discharge. Publicly reported scores will be utilized as a proxy for patient satisfaction [ 70 ]. The HCAHPS data used in this study were collected independently from the other patient data and represented the publicly reported satisfaction scores for the participating hospitals during the study period.

Electronic Medical Records (EMR)

Electronic Medical Records (EMRs) served as a data source to extract 30-day hospital readmission rates, an objective measure that is pivotal to evaluating health outcomes in relation to nursing incivility, nurse stress, and patient engagement. Utilization of EMRs facilitates the collection of this crucial metric, allowing for a rigorous assessment of potential associations between the aforementioned variables and patient health outcomes, as reflected in readmission rates within 30 days after discharge.

Ethics approval

The study received ethical approval from the General Directorate of Health Affairs, Hail Healthy Cluster, Hail Region / IRB Registration Number with KACST, KSA: H-11–08 L-074 / IRB log number 2023-66. The approval process involved evaluating the study’s objectives, methods, instruments, and impacts while emphasizing adherence to ethical principles like respect, justice, beneficence, and non-maleficence. A detailed informed consent form was prepared to ensure the understanding and voluntary participation of the participants, along with measures to maintain privacy and confidentiality using unique participant identifiers. The protocol also included provisions for participant transparency, including the right to access results and withdraw at any time without repercussions. Following the review of the IRB, ethical clearance was granted, allowing the study to proceed in accordance with established ethical standards and guidelines.

Data collection was conducted between May 2023 and November 2023 in four public hospitals located in the northwest region of Saudi Arabia. These hospitals were strategically selected to represent the region’s geographic and demographic diversity, ensuring the sample reflected the wider context of Saudi healthcare. Nurses were recruited through targeted invitations sent to all eligible personnel, aiming for a broad representation of experiences and backgrounds. Patients were randomly selected from hospital records and invited to participate voluntarily. No incentives were offered to participants.

Paper-based surveys were administered to both nurses and patients. Nurses completed the surveys during their work shifts, while patients were surveyed independently of their hospital stay. Researchers were available to assist participants who needed clarification or faced difficulty understanding the questions. Patients completed the PAM and MMAS-8 surveys independently, typically within 2–4 weeks after discharge, to assess their activation levels and medication adherence during the post-hospitalization period.

The data collection process was designed to ensure participant privacy, reduce potential biases, and gather comprehensive responses without causing undue burden. Unique participant identifiers were assigned to each nurse and patient to maintain confidentiality throughout the study. All collected data were stored on secure, password-protected servers, with access restricted to authorized members of the research team. Physical copies of the surveys were stored in locked cabinets, and electronic data were encrypted to prevent unauthorized access.

Participants typically spent 15–20 min completing the surveys, which included the Nursing Incivility Scale (NIS) and the Perceived Stress Scale (PSS) for nurses, and the Patient Activation Measure (PAM) and the Morisky Medication Adherence Scale (MMAS-8) for patients. These instruments were selected based on their established validity and reliability in similar research contexts and their alignment with the study variables. The data collection process was designed to ensure participant privacy, reduce potential biases, and gather comprehensive responses without causing undue burden. The use of paper-based surveys accounted for participants’ varied preferences and technological comfort levels while minimizing potential technical issues.

Statistical analysis

This study employed descriptive statistics to establish the demographic profiles of nurse and patient participants, summarizing categorical variables through frequencies and percentages. For the Nursing Incivility Scale (NIS) and Perceived Stress Scale (PSS), we divided scores into tertiles for descriptive analyses, which offered an intuitive understanding of incivility and stress levels among participants. In our regression analyses, we used the continuous scores to preserve the rich variability inherent in these measures.

The statistical examination commenced with bivariate Pearson’s correlation analysis, identifying foundational relationships between key study variables. We then conducted multiple linear regression models to determine the direct effects of nursing incivility, nurse stress, patient activation, and medication adherence on health outcomes. Hierarchical multiple regression analyses were conducted, entering nursing role as a covariate in the first step, followed by the predictor variables (nursing incivility, nurse stress, patient activation, and medication adherence) in subsequent steps.

Further statistical exploration involved mediation analyses to investigate the indirect effects within our conceptual framework. Specifically, we examined the mediating role of nurse stress in the association between nursing incivility and health outcomes and the potential mediation of patient engagement between nurse stress and health outcomes. A serial mediation model elucidated the complex interplay and indirect pathways that link nursing incivility to patient outcomes through multiple mediator variables.

All statistical procedures were executed using SPSS Version 26. Missing data were managed via mean substitution for subscale averages. To ensure participant privacy and confidentiality, all analyses were performed using de-identified data, with unique participant identifiers replaced by numeric codes. Only aggregate results were reported, ensuring that no individual participant could be identified from the study findings. The significance threshold was set at an alpha level of 0.05, and effect sizes were calculated to contextualize the strength of associations.

Consistent with the structured complexity of our theoretical model, a serial mediation analysis was incorporated into the statistical strategy. This analysis enabled us to dissect the multi-step indirect effects and examine the potential sequential mediators, providing an integrated understanding of the relationships among the constructs of interest. The integrity of the analyses was maintained by stringent testing for normality, linearity, and homoscedasticity, ensuring the appropriateness of our regression models and the robustness of our findings. The analytical choices, carefully aligned with the objectives of the study and the nature of the data, facilitated a clear depiction of the causal pathways and supported the validity of our conclusions.

This section presents the empirical findings of the study, which aim to explore the relationships between nursing incivility, nurse stress, patient engagement, and health outcomes. The results are based on data from 289 nurses and 521 patients in four hospitals. Detailed statistical analyses, including descriptive statistics, correlations, and regression models, help to elucidate these relationships. The following tables provide a comprehensive summary of these analyses, shedding light on the nuances and key takeaways of the study findings. The scales used in this study demonstrated good to excellent reliability in the current sample. Cronbach’s alpha coefficients were as follows: Nursing Incivility Scale (NIS) α = 0.94, Perceived Stress Scale (PSS) α = 0.82, Patient Activation Measure (PAM) α = 0.89, and Morisky Medication Adherence Scale (MMAS-8) α = 0.79.

The demographic characteristics presented in Table 1 offer a comprehensive statistical overview of the study participants, encompassing both nurses ( N = 289) and patients ( N = 512). The age distribution among nurses is skewed toward younger age groups, with 38.7% aged 25–30 years and 30.1% aged 31–40 years. In contrast, the patient population exhibits a more evenly distributed age range, with the highest proportion (37.1%) in the 31–40 age group. Gender-wise, the nurse sample is predominantly female (66.8%), aligning with the traditional gender demographics of the nursing profession, while the patient sample shows a more balanced distribution (51.6% male, 48.4% female). The nursing roles represented include Registered Nurses (51.9%), Head Nurses (24.2%), and Supervisors (23.9%), reflecting a diverse representation of nursing staff. In terms of experience, the majority of nurses (51.6%) have 2–5 years of experience, followed by those with more than 5 years (25.3%) and less than 2 years (23.2%). The patient health status data reveals that 63.7% are categorized as healthy, 33.6% have a managed chronic condition, and 2.7% have an unmanaged chronic condition. Furthermore, the educational qualifications of nurses are well-represented, with 62.0% holding a Bachelor’s degree and 38.0% possessing a Master’s or Ph.D. degree. Finally, the distribution of participants across the four hospitals is relatively even, ranging from 24.4 to 25.8% for patients and 24.2–25.6% for nurses, ensuring a representative sample from various healthcare settings.

Table 2 presents a quantitative assessment of the severity distribution of nursing incivility scores among the nurse participants. The Nursing Incivility Scale (NIS) scores have been categorized into three distinct levels: mild incivility (scores ranging from 0 to 33), moderate incivility (scores ranging from 34 to 66), and severe incivility (scores ranging from 67 to 100). Out of the total 289 nurse participants, 90 (31.1%) reported experiencing mild levels of incivility, 125 (43.3%) experienced moderate incivility, and 74 (25.6%) experienced severe incivility. The data reveals that a significant proportion of nurses, nearly 69%, reported experiencing moderate to severe levels of incivility in their workplace, highlighting the prevalence of this issue within the nursing profession. The distribution of incivility levels provides a quantitative representation of the severity of the problem, which is crucial for developing targeted interventions and policies to address workplace incivility and promote a positive work environment for nurses.

Table 3 presents the distribution of Perceived Stress Scale (PSS) scores among the nurse participants, categorized into three levels: low stress (scores ranging from 0 to 13), moderate stress (scores ranging from 14 to 26), and high stress (scores ranging from 27 to 40). Out of the total 289 nurse participants, 95 (32.9%) reported low stress levels, 120 (41.5%) reported moderate stress levels, and 74 (25.6%) reported high stress levels. The data reveals that a significant proportion of nurses, approximately 67%, experienced moderate to high levels of stress, indicating the presence of substantial stress among the nursing workforce. The distribution of stress levels provides a quantitative representation of the prevalence and severity of stress experienced by nurses, which is crucial for developing targeted interventions and strategies to address and mitigate stress within the nursing profession.

Table 4 presents a comparative analysis of patient activation levels and medication adherence, as measured by the Patient Activation Measure (PAM) and the Morisky Medication Adherence Scale (MMAS-8), respectively. The scores for both measures are categorized into low/poor, moderate, and high ranges. For the PAM, the score ranges are 0–33 for low/poor activation, 34–66 for moderate activation, and 67–100 for high activation. The table shows that 150 patients scored in the low/poor range, 250 in the moderate range, and 112 in the high range. For the MMAS-8, the score ranges are 0–2 for low/poor adherence, 3–5 for moderate adherence, and 6–8 for high adherence. The table indicates that 200 patients scored in the low/poor range, 180 in the moderate range, and 132 in the high range. The table also provides p-values for the comparison between the low/poor and high categories for both measures. For the PAM, the p-value is reported as < 0.05, indicating a statistically significant difference between the low/poor and high activation groups. For the MMAS-8, the p-value is reported as < 0.01, suggesting a highly significant difference between the low/poor and high medication adherence groups.

Table 5 presents the bivariate correlation coefficients among the key study variables: Nursing Incivility (NIS), Nurse Stress (PSS), Patient Activation (PAM), and Medication Adherence (MMAS-8). The table is structured as a correlation matrix, where each cell represents the correlation coefficient between the corresponding row and column variables. The diagonal elements (1.00) represent the perfect correlation of each variable with itself. The correlation coefficient between Nursing Incivility (NIS) and Nurse Stress (PSS) is 0.45, indicating a moderate positive correlation. The correlation coefficients between Nursing Incivility (NIS) and Patient Activation (PAM), and Nursing Incivility (NIS) and Medication Adherence (MMAS-8) are − 0.30 and − 0.25, respectively, suggesting moderate negative correlations. The correlation coefficient between Nurse Stress (PSS) and Patient Activation (PAM) is -0.40, indicating a moderate negative correlation. The correlation coefficient between Nurse Stress (PSS) and Medication Adherence (MMAS-8) is -0.35, suggesting a moderate negative correlation. The correlation coefficient between Patient Activation (PAM) and Medication Adherence (MMAS-8) is 0.60, indicating a strong positive correlation.

Table 6 presents a nuanced understanding of how various factors related to nursing and patient engagement influence health outcomes, specifically 30-day readmission rates and patient satisfaction scores. The data indicate that nursing incivility has a detrimental effect on both health outcomes, suggesting that interventions aimed at reducing workplace incivility may improve patient care. Interestingly, nurse stress shows a positive correlation with both outcomes, indicating that higher stress levels could be linked to more frequent patient follow-up, possibly improving patient satisfaction despite higher readmission rates. This points to the complex role of stress in healthcare settings. Furthermore, patient activation is strongly negatively correlated with both outcomes, emphasizing the benefits of patient empowerment in their own care processes. Enhanced patient activation could lead to fewer readmissions and higher satisfaction. Similarly, medication adherence, which is negatively associated with readmission rates and positively with satisfaction scores, highlights its critical role in effective patient management. These insights reveal the interconnected nature of healthcare environments and underscore the importance of a multifaceted approach to improving patient outcomes.

Table 7 presents an intricate statistical investigation into the cascading effects of nursing incivility within a healthcare setting. The analysis thoughtfully dissects how nursing incivility impacts patient outcomes, notably through nurse stress and patient engagement mediating variables. The positive estimate (B = 0.08) for the path from nursing incivility to nurse stress, with a significant p-value of less than 0.001, underscores the strong influence of workplace incivility on nurse stress. Furthermore, both statistically significant, the adverse pathway from nursing incivility to patient engagement (B = -0.24) and from nurse stress to patient engagement (B = -0.41) highlights a detrimental cascade effect, where incivility indirectly undermines patient engagement through increased nurse stress. The substantial direct impact of patient engagement on patient outcomes (B = 0.52) emphasizes the critical role of patient involvement in their care. The analysis culminates in delineating the total and direct effects of nursing incivility on patient outcomes, with the indirect effects through nurse stress and patient engagement providing a deeper understanding of the underlying dynamics. The obtained relationships between nursing incivility, nurse stress, patient engagement, and health outcomes, along with their standardized regression coefficients (β) and significance levels (p-values), are visually summarized in Fig. 2 .

As illustrated in Fig. 2 , nursing incivility had a significant direct effect on both nurse stress (β = 0.08, p < 0.001) and patient engagement (β = -0.24, p = 0.003). Nurse stress, in turn, negatively influenced patient engagement (β = -0.41, p < 0.001). Furthermore, patient engagement had a strong positive impact on patient outcomes (β = 0.52, p < 0.001). The total effect of nursing incivility on patient outcomes was significant (β = -0.37, p < 0.001), with both direct (β = -0.22, p = 0.002) and indirect effects through nurse stress and patient engagement (β = -0.15, p = 0.004) contributing to this relationship. These findings provide evidence for the hypothesized cascading effects of nursing incivility on patient outcomes, highlighting the crucial role of nurse stress and patient engagement as mediating factors in this relationship. The results underscore the importance of addressing workplace incivility and promoting a positive work environment to enhance nurse well-being, patient engagement, and ultimately, patient outcomes.

Relationships between nursing incivility, nurse stress, patient engagement, and health outcomes were obtained, with standardized regression coefficients (β) and significance levels ( p -values)

Additional analyses were conducted to examine potential differences in experiences of nursing incivility and stress among staff nurses, head nurses, and supervisors. One-way ANOVA tests revealed significant differences in NIS scores across nursing roles [F(2, 286) = 5.67, p = 0.004]. Post-hoc comparisons using Tukey’s HSD test indicated that staff nurses (M = 48.3, SD = 18.6) reported significantly higher levels of incivility compared to supervisors (M = 39.5, SD = 16.2, p = 0.003). However, no significant differences were found in PSS scores across nursing roles [F(2, 286) = 1.45, p = 0.236].

The additional analyses revealed significant differences in Nursing Incivility Scale (NIS) scores across nursing roles [F(2, 286) = 5.67, p = 0.004], with staff nurses (M = 48.3, SD = 18.6) reporting significantly higher levels of incivility compared to supervisors (M = 39.5, SD = 16.2, p = 0.003). To account for the potential influence of nursing role on the overall results, we included it as a covariate in subsequent regression analyses.

To further examine the robustness of our findings, we conducted a sensitivity analysis by removing head nurses and supervisors from the sample and re-running the analyses with only staff nurses. The results remained consistent with the original findings, suggesting that the observed relationships between nursing incivility, nurse stress, patient engagement, and health outcomes were not unduly influenced by the inclusion of head nurses and supervisors in the sample.

This cross-sectional study examined the relationships between perceived nursing incivility, nurse stress levels, patient engagement in care, and patient health outcomes. The findings reveal a multifaceted relationship where nursing incivility is directly detrimental to nurses’ well-being and indirectly affects patient outcomes through the mediating effects of nurse stress and patient engagement.

The positive correlation between nursing incivility and nurse stress aligns with previous research indicating that workplace incivility can lead to negative psychological outcomes and job dissatisfaction [ 71 , 72 , 73 , 74 , 75 ]. The findings here extend this understanding by quantifying the correlation and delineating the impact of different levels of incivility.

In contrast, some studies, such as [ 6 , 76 ], have suggested that certain coping mechanisms and organizational cultures can mitigate the impact of incivility on stress. However, this study highlights the widespread nature of incivility in nursing, suggesting that such coping strategies may not be sufficient in the face of severe or persistent incivility. The inverse relationship between nurse stress and patient engagement supports the notion that stressed nurses may be less able to effectively engage with patients, aligning with research [ 51 ], which showed that nurse burnout could lead to decreased quality of patient care. Conversely, a study [ 52 ] found that certain aspects of nurse engagement, like job satisfaction, could buffer the impact of stress on patient care. However, this study suggests that the stress level resulting from incivility can override such positive aspects of engagement.

The negative impact of nursing incivility on patient health outcomes, evidenced by increased readmission rates within 30 days and lower patient satisfaction scores, is consistent with previous findings [ 6 , 76 ]. This reinforces the idea that the nursing work environment, including the presence or absence of incivility, can directly influence patient outcomes such as readmission rates and satisfaction scores, which were measured at the 30-day mark in our study.

However, research [ 12 , 28 ] argued that the impact of the nursing work environment on patient outcomes is often indirect and moderated by other factors. This study refines this perspective by demonstrating a direct correlation, suggesting that the impact of incivility is immediate and significant [ 57 , 58 , 59 ]. underscore incivility as a significant workplace stressor that nurses face that can adversely affect their well-being. The severity analysis further highlights that a concerning 25.6% of nurses report experiencing severe incivility, while 43.3% encounter moderate levels. Such widespread uncivil behaviors from colleagues, supervisors, physicians, and patients create stressful work environments that diminish the ability of nurses to perform effectively [ 11 ].

However, contrary to some studies [ 8 , 77 ], our mediation analysis reveals only a moderate total effect size (β = -0.05) of nursing incivility on patient outcomes. This discrepancy could reflect cultural specificities within Saudi hospitals that shape inter-action dynamics differently than their western counterparts. However, the negative association remains noteworthy. In addition, stress exhibits an unexpected positive association with patient outcomes. This surprising finding warrants a deeper ethnographic investigation to elucidate the complex stress and coping mechanisms of nurses within the hospitals sampled that unexpectedly improved patient care. Critically, patient engagement registers the strongest impact on health outcomes (β = 0.52) [ 2 , 78 , 79 ]. Interestingly, 63.7% of patients fall under the ‘Healthy’ category, although 33.6% manage chronic conditions. This breakdown provides a favourable foundation for boosting patient activation efforts. However, the correlation and regression analyses reveal that improvements in workplace conditions for nurses could further improve patient engagement and care quality.

The study findings on the mediator effect of nurse stress, linking nursing incivility with poorer patient outcomes, add a new dimension to the existing literature. This aligns with the work of [ 12 ], who emphasized the importance of the emotional well-being of healthcare providers in ensuring patient safety. This contrasts with some views like those presented [ 6 ], who posited that organizational factors play a more substantial role in mediating the impact of incivility on outcomes. Our study suggests that individual stress levels are equally, if not more, critical in this context. The serial mediation analysis reveals the pathway from nursing incivility through nurse stress to patient engagement and outcomes, and it presents a comprehensive model that integrates various aspects of the nursing environment. This model is supported by research [ 6 ], which also emphasises the cascading effects of workplace dynamics on patient care. However, this finding challenges the argument [ 22 ] that the primary impact of the nursing environment on patient outcomes is through organizational efficiency rather than staff well-being.

Conclusions

This cross-sectional study conducted in four Saudi Arabian hospitals examined the complex relationships between nursing incivility, nurse stress, patient engagement, and health outcomes. The findings underscore the widespread impact of nursing incivility, which adversely affects nurse well-being and, through increased nurse stress, indirectly influences patient outcomes. Specifically, our analyzes demonstrate that nursing incivility is related to higher readmission rates at 30 days and lower patient satisfaction scores, providing concrete examples of its negative ramifications.

Our empirical evidence, derived from validated scales and robust multivariate regression analyzes, confirms that nursing incivility increases stress levels among nurses, corroborating existing literature that identifies uncivil behavior as a significant workplace stressor. In particular, more than two thirds of the participants reported experiencing moderate to severe levels of incivility, highlighting the widespread nature of this issue within healthcare settings. Theoretically, this research enriches the current understanding of the impacts of nursing incivility by situating them within a comprehensive framework that includes both direct and indirect effects on health outcomes.

Practically, the study lays a solid foundation for developing targeted interventions aimed at cultivating more respectful and collaborative nursing environments. Such interventions could include training programs focused on conflict resolution and stress management, which are critical to mitigating the effects of incivility and improving overall quality of care. Future research should explore the longitudinal effects of nursing incivility to better understand the causality and persistence of its impacts. Additionally, investigating the role of organizational factors such as leadership styles and workplace culture in modifying or exacerbating the effects of incivility could provide deeper insight into effective strategies to improve nurse and patient outcomes.

Limitations

The limitations of the study provide avenues for further research. Longitudinal approaches could establish causal claims more firmly. A longitudinal design that follows participants over an extended period could provide more insights into the temporal aspects of these relationships and strengthen our understanding of the causality between nursing incivility, nurse stress, patient engagement, and health outcomes.

Another limitation refers to the representativeness of the sample. Although efforts were made to ensure diversity through a combination of random sampling and voluntary participation, the generalizability of the findings may be limited. The study was conducted in four public hospitals in the northwest region of Saudi Arabia, and the unique cultural and socioeconomic characteristics of this region should be considered when interpreting the results and their implications for nursing practice and patient care. Future studies could explore these relationships in different healthcare settings, regions, and cultural contexts to assess the generalizability of the findings.

Furthermore, the current study did not investigate the role of organizational factors in contributing to nursing incivility, stress, and patient outcomes. While focusing on individual-level variables provides valuable insights, a more comprehensive understanding would require the inclusion of organizational factors such as leadership, communication, and workplace culture. Future research should aim to incorporate these measures to gain a holistic perspective on the relationships between nursing incivility, stress, and patient outcomes.

Practical implications and future directions

The findings of this study have significant practical implications, providing an evidence base for healthcare institutions to develop systemic strategies to address nursing incivility and its cascading impacts. Interventions should focus on cultivating positive workplace cultures, deescalating incivility through protocols, facilitating team building, and implementing self-care training. Regarding patients, patient education programs to promote activation and specialist referrals to improve adherence appear prudent. Future studies could build on these findings by testing such interventions through experimental or action methodologies to quantify long-term results.

Future research could also explore the role of organizational factors in contributing to nursing incivility, stress, and patient outcomes. Investigating aspects such as leadership styles, communication patterns, and workplace culture could provide valuable insights into the systemic elements that shape the dynamics of nursing incivility and its consequences. By examining the interaction between individual and organizational factors, future studies could offer a more holistic understanding of the complex relationships at play and inform the development of targeted interventions at the individual and organizational levels.

Related research might explore subgroup differences in perceptions by age or unit type or investigate relationships in private-sector hospitals compared to these public institutions. Furthermore, examining the broader organizational impact of nursing incivilities, such as its effects on team dynamics, staff turnover, and general healthcare culture, would contribute to a more comprehensive understanding of the phenomenon. Assessing the economic implications of incivility, including costs associated with staff replacement and lost productivity, could highlight the financial burden on healthcare organizations and inform strategic decisions to address this issue. Future studies could also employ qualitative methods to gain deeper insights into nurses’ experiences of incivility and its impact on their well-being and professional practice. As the Saudi healthcare system continues to evolve, mitigating workplace mistreatment and nurturing patient engagement will only grow in importance, making this study highly relevant.

Availability of data and materials

Data will be available upon request.

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Institutional review board statement

This study was carried out with the approval of the General Directorate of Health Affairs, Hail Healthy Cluster, Hail Region / IRB Registration Number with KACST, KSA: H-11–08 L-074 / IRB log number 2023-66.

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Informed consent was obtained from all participants involved in the study.

The Deanship of Scientific Research funded this work at Jouf University through the Fast-Trace Research Funding Program.

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O.M.E.R. contributed to the conception and design of the study, recruited patients, collected and analyzed data, interpreted the results, and drafted the manuscript. N.A.A. contributed to the study design, data collection, result analysis and interpretation, and manuscript review. M.A. contributed to patient recruitment, data collection, and manuscript review. All authors approved the final version of the manuscript.

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Alsadaan, N., Ramadan, O.M.E. & Alqahtani, M. From incivility to outcomes: tracing the effects of nursing incivility on nurse well-being, patient engagement, and health outcomes. BMC Nurs 23 , 325 (2024). https://doi.org/10.1186/s12912-024-01996-9

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Persistent organic pollutants in the natural environments of the city of Bratsk (Irkutsk Oblast): Levels and risk assessment

Degradation, Rehabilitation, and Conservation of Soils
Published: 06 November 2014
Volume 47 , pages 1144–1151, ( 2014 )

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E. A. Mamontova 1 ,
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The contents of persistent organic pollutants (POPs)—polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs)—in the natural environments of an industrial city (Bratsk) of Irkutsk oblast have been studied. Features of the spatial and seasonal distribution of the PCBs and OCPs in the soils and the atmospheric air have been revealed. The structure of the homological and congeneric composition of the PCBs in the soils and the atmospheric air has been shown. Parameters of the carcinogenic and noncarcinogenic risks for human health from the impact of the PCBs and OCPs present in the soils and the atmospheric air have been determined.

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Original Russian Text © E.A. Mamontova, E.N. Tarasova, A.A. Mamontov, 2014, published in Pochvovedenie, 2014, No. 11, pp. 1356–1364.

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Mamontova, E.A., Tarasova, E.N. & Mamontov, A.A. Persistent organic pollutants in the natural environments of the city of Bratsk (Irkutsk Oblast): Levels and risk assessment. Eurasian Soil Sc. 47 , 1144–1151 (2014). https://doi.org/10.1134/S1064229314110076

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DOI : https://doi.org/10.1134/S1064229314110076

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The Current Territorial Differentiation of the Industry of Irkutsk Oblast

N. a. ippolitova.

1 Sochava Institute of Geography, Siberian Branch, Russian Academy of Sciences, 664033 Irkutsk, Russia

2 Irkutsk State University, 664003 Irkutsk, Russia

M. A. Grigoryeva

This article discusses recent changes in the development of industrial production in Irkutsk oblast from 2010 to 2019. Industry is the basic component in the economic complex; it provides about half of the region’s gross added value and is characterized by a multi-sectoral structure formed primarily on the basis of using natural resources and cheap electricity. It is pointed out that in the last decade, a significant change in the structure of industry has led to a structural simplification of its sectoral composition with a significant shift toward the raw materials sector. Cities remain the leading centers of concentration of the manufacturing industry. The grouping of municipalities according to the level of industrial development was carried out according to the available statistical data: the calculated share of the employed in industry and the volume of shipped products of large and medium-sized organizations. On the basis of their ratio, groups of regions with intensive development of the extractive industries, primarily the oil and gas sector, as well as territories in which the industrial profile was formed in Soviet times but underwent transformations under the influence of changes in the market, were identified. A group of regions with very low industrial development has been identified, in which economic activities are mainly related to agriculture, logging, transport, and tourism. It is shown that some of the municipalities have changed their position in the groups when compared to 2010. The rest of the composition is relatively stable. It was found that in the first and fourth groups a change in priority in the development of types of economic activity occurred, whereas the second and third groups show a change in their proportions. Large business contributes to the extremely uneven distribution of investments across the oblast in the implementation of investment projects.

INTRODUCTION

Irkutsk oblast, one of the key industrial regions of Siberia, has great industrial and natural resource potential, which, together with its competitive advantages, make it possible to occupy a leading position among other regions of the country. Research by N.N. Klyuev [ 1 ] shows that Irkutsk oblast is one of the ten Russian regions that maximized the volume of industrial production from 1990 to 2017.

The modern industrial structure of Irkutsk oblast is made up of several basic industries, including the electric power industry, mining and timber processing complexes, nonferrous metallurgy, chemical and petrochemical industries, as well as mechanical engineering and metalworking. With the start of oil and gas production, the oil and gas industry has developed.

Currently, the spatial development of Irkutsk oblast is based on large territorial production centers located in Irkutsk, Bratsk, Shelekhov, Angarsk, Sayansk, Ust-Ilimsk, Zheleznogorsk-Ilimsk, Taishet, Ust-Kut, and Bodaibo, where over 55% of the region’s population lives. These territories account for more than 85% of the added value produced in the region, and about 60% of investments [ 2 ].

The development of industrial production and its territorial features have been widely considered by domestic geographers at different times. It is worth noting the works devoted to the period of industrialization of the eastern territories [ 3 ], economic development [ 4 ], and issues of the location and development of certain industries [ 5 , 6 ]. In recent years, the main attention has been paid to the study of industry in the sectoral context [ 7 – 11 ], as well as using the theory of territorial production complexes [ 12 , 13 ]. The use of an integrated approach makes it possible to determine structural changes in the industry of the regions [ 14 ].

At the regional level, there are many methods and approaches to the construction of typologies and groupings for the socioeconomic development of territories, and in particular industrial development. Consideration of the intraregional level of industrial development in the scientific literature is less common, for example [ 15 – 18 ], which increases the relevance of this research, which is of an applied nature.

MATERIALS AND METHODS

The information base of the study, which covers 2010–2019, was the materials of the Federal State Statistics Service, including databases of indicators of municipalities and official sites of local governments (analytical and forecast reports).

It is assumed in this work that at present industrial production includes the following sections of OKVED-2: Extraction of minerals (B); Manufacturing industries (C); Provision of electricity, gas and steam; air conditioning (D); Water supply; sewerage, waste collection, and disposal, and pollution elimination activities (E). According to OKVED, in 2010 industrial production consisted of the following types of activities: Extraction of minerals (C); Manufacturing (D); Production and distribution of electricity, gas, and water (E). We note that the work did not take into account the subsection Forestry and logging, which is included in the section Agriculture, forestry, hunting, fishing, and fish farming (A), although logging is a specialization of individual municipalities of the region.

The statistical data used at the municipal level (shipped goods of its own production, performed works and services on its own; the average number of employees of organizations by type of economic activity; investments in fixed assets) are given by Rosstat for large and medium-sized organizations, excluding small businesses. For example, the difference between the volume of products shipped for large and medium-sized organizations and for the full range of organizations is 5.6%, and for those employed in industrial production it is about 15%.

Due to the fact that according to the indicator called shipped goods of our own production, performed works and services on our own (without subjects of municipalities), information on certain types of economic activity is not published for 29 out of 42 municipalities of Irkutsk oblast in order to ensure the confidentiality of primary statistical data [ 19 ], the materials posted on the official websites of the corresponding municipalities were taken into account.

This work used comparative geographical and statistical research methods.

RESULTS AND DISCUSSION

In the structure of gross value added in Irkutsk oblast, industry accounted for 31.7% in 2010, and 44.8% in 2018. The specific weight of the volume of shipped products of the region in Russia increased from 1.4% in 2010 to 1.7% in 2019, due to the fact that the volume of mining operations increased nine times. The average annual number of workers employed in the industrial sector decreased by 3.6%.

In 2010–2019, the production index in Irkutsk oblast, based on the results of its retrospective recalculation by Rosstat, did not fall below 100%, reaching its maximum value in 2010, 113.3%, and the minimum value in 2019, 100.4% ( Fig. 1 ). Growth rates of the industrial production index in 2010–2012, were due to significant volumes of mining (especially hydrocarbons). The drop in production volumes in 2019 is associated with a decrease in the production of crude oil, metal ores, and due to the current federal emergency in the region in the summer of 2019 (flooding of settlements) and coal. The trend continued in 2020 under the influence of external and internal factors (Russian participation in the agreement with the OPEC + countries and, accordingly, the restriction on oil production, as well as restrictions on the part of Russian Railways in accepting coal for export). Against the background of this situation, the manufacturing industry in 2020, in contrast, showed an increase in production (in particular, the contribution was made by Pharmasynthez, which began to produce medicines for the treatment of coronavirus infection).

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The production indices of Irkutsk oblast, %. Types of economic activity: 1 , industrial production; 2 , mining; 3 , manufacturing; 4 , supply of electricity, gas and steam; air conditioning.

Transformational processes, which differ in intensity and direction in different periods, have formed the modern structure of the region’s industry, whose leading industries are: extraction of crude oil and natural gas, which accounts for 35.2% of the volume of shipped products; energetics , 10.3; metallurgical production, 9.1; production of paper and paper products, 4.7; wood processing, 4.5%. In 2010, the leading positions were occupied by the energy sector, 18.3%; production of machinery, equipment, vehicles, 16.3; metallurgical production, 15.3; extraction of fuel and energy minerals, 8.9; and chemical production, 7.6%.

The average number of employees of organizations (excluding small businesses) and the volume of goods, works, and services shipped by large and medium-sized organizations were used as indicators that characterize the level of development of industrial production in 42 regional municipalities in 2010 and 2019.

The ratio of these indicators made it possible to distinguish four groups of municipalities by the level of industrial development (high, medium, low, and very low) in 2010 and 2019. ( Figs. 2, 3 ).

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The distribution of the share of people employed in industry and the volume of industrial production of large and medium-sized organizations in Irkutsk oblast in 2010

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The distribution of the share of employed in industry and the volume of industrial production of large and medium-sized organizations in Irkutsk oblast in 2019

In 2019, compared to 2010, there was a transition of a number of territories of the region from one group to another. In three municipalities (Ust-Kutsky, Katangsky, and Alarsky districts) there was an increase in the level of industrial development, and in the other three municipalities (Angarsk, Shelekhovsky district, and Usolye-Sibirskoe) a decrease occurred.

The Highly developed group (Katangsky, Ust-Kutsky regions, and Bratsk) is characterized by high values of the share of people employed in industrial production and the volume of shipped products. It accounts for 21.2% of those employed in industrial organizations of the region (rotation work is also used) and 48.4% of investments in fixed assets. The northern regions continue to increase their concentration of the volume of shipped products in the region by the type of economic activity mining (2010, 43.8%; 2019, 73.6%). Oil and gas condensate production increased by 5.4 times, from 3.3 million tons in 2010 to 17.9 million tons in 2019. Oil produced from fields in the north of the region is fed to the Eastern Siberia–Pacific Ocean (ESPO) pipeline system; it is delivered to the Far East and then exported to China and other countries of the Asia–Pacific region. The main companies represented on the territory of these municipalities are Verkhnechonskneftegaz, Dulisma, and the Irkutsk Oil Company. The latter is the largest taxpayer to the regional budget (in 2018, the share of its contributions was 12.5%). Generally, oil producing enterprises provided 46% of all income tax revenues in 2018 in the structure of tax revenues of the consolidated budget of the region.

Industrial production in Bratsk is associated with the activities of such processing enterprises as RUSAL Bratsk (in 2019 it provided 38% of the aluminum production in Russia), the Ilim Group in Bratsk, and the Bratsk Ferroalloy Plant, which form the industrial image of the city. During the period an increase in the volume of shipped products in the manufacturing sector was noted in Bratsk (2010, 22.6%; 2019, 29.9%), which allows it to remain a large industrial hub of the region.

Group with an average level of development (the Angarsk, Svirsk, Sayansk, Ust-Ilimsk, Irkutsk, Bodaibinsky, Shelekhovsky, Nizhneilimsky, and Tulunsky districts) is distinguished by a high share of those employed in industry and an average volume of industrial production. About half of the region’s population lives in these municipalities, they produce 40.6% of industrial production, and concentrate 61.5% of those employed in the industrial sector, as well as 38.4% of investments. The group includes almost all major industrial centers in the region. Unlike the previous case, the sectoral composition of this group is more diverse and is represented by enterprises of nonferrous metallurgy, mechanical engineering, chemical and petrochemical, pulp and paper, nuclear, pharmaceutical, and food industries (Irkutsk Aluminum Plant, Irkutsk Aviation Plant, Angarsk Petrochemical Company, Angarsk Polymer Plant, Sayanskkhimplast, Ilim Group in Ust-Ilimsk, Angarsk Electrolysis Chemical Plant, Pharmasintez, etc.). The production profile of these territories was formed back in the Soviet era, but at the present stage enterprises continue to play a significant role in the socioeconomic development of the region, especially for export-oriented industries.

The mining sector is represented by gold mining at ore and alluvial deposits (Polyus Verninskoe, Vysochaishy, Druza, Lenzoloto, etc., which provided more than 9% of the gold mining in Russia), iron ore (Korshunovsky GOK), and coal (Tulunugol open pit).

A separate place in this group is occupied by Irkutsk, the administrative center of the region with a diversified industry, which is the center of the emerging agglomeration of the same name. For Irkutsk, there is a significant increase in shipped products by the type of economic activity supply of electricity, gas, and steam, and air conditioning (in 2010, 27.9%, and in 2019, 87.4%). This increase is explained by a peculiarity of statistical accounting: most of the products produced on the territory of the region for this type of economic activity are attributed to the city. In reality, Irkutsk produces 25 times less of them. We note that almost all large energy companies, except for Vitimenergo, are registered in the regional center.

The low development group (Usolye-Sibirskoe, Winter, Tulun, Cheremkhovo, Kirensky, Zhigalovsky, Nizhneudinsky, Usolsky, Mamsko-Chuisky, Zalarinsky, Kazachinsko-Lensky, Taishetsky, Ust-Ilimsky, Bratsky, Nukutsky, Alarsky, Slyudyansky, Chunsky, Chunkhovsky, and Irkutsky) is the most numerous and heterogeneous in its composition. It is characterized by a small share of those employed in the industrial production of the region and a low volume of goods shipped. This group accounts for 8.8% of the volume of shipped goods, works, and services of the region, 16.8% of those employed in industry, and 12.7% of investments. In more than half of the municipalities, the leading type of economic activity is manufacturing, which is represented by medium-sized and large companies: a branch of the Ilim Group in the Bratsk District, Knauf Gips Baikal, Rusforest Magistralny, Usolye Salt Extraction and Processing Shop (part of Russol), and others.

Mining predominates in six municipalities (Gazprom Dobycha Irkutsk, IOC, Nedra mining company (GPK), Tyretsky salt mine, Cheremkhovugol open pit, etc.); in Tulunsky district, it is power engineering, and in Mamsko-Chuysky, it is water supply. At the end of 2022, gas is planned to be supplied from the Kovykta field (Irkutsk gas production center) to the Power of Siberia gas trunkline, which is oriented to external consumption (China).

The group includes territories both with industrial enterprises closed in the post-Soviet period and with new industrial facilities that have just begun to function. Single-industry towns (Usolye-Sibirskoye, Cheremkhovo, and Tulun) were given the status of a territory of advanced socioeconomic development to support the economy.

The very low development group (Osinsky, Kuytunsky, Bayandaevsky, Olkhonsky, Balagansky, Kachugsky, Bokhansky, Ekhirit-Bulagatsky, Ust-Udinsky, and Ziminsky districts). This accounts for only 0.1% of the volume of products produced in the region, 0.5% of those employed in industrial organizations of the region, 0.5% of investments in fixed assets. The industry is mainly represented by food. The districts specialize in agriculture, logging, and recreational activities. There are no large companies; small business prevails.

In the first and fourth groups, the priorities in the development of types of economic activity changed, and in the second and third groups, their proportions changed ( Fig. 4 ).

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The change in the structure of types of economic activities by groups of municipalities of Irkutsk oblast in 2010 and 2019, %. Types of economic activity: 1 , mining; 2 , manufacturing industries; 3 , supply of electricity, gas and steam; air conditioning; 4 , water supply, sewerage, waste collection and disposal, activities to eliminate pollution.

From 2010 to 2019, the volume of shipped products and investments increased by 3.4 and 3.8 times, respectively (on average per one municipal district) (see Table 1 ), with a decrease in the population and employed in the industrial sector. The greatest change in these indicators is noted in the first and second groups.

Industrial development indicators by groups of municipalities of Irkutsk oblast in 2010 and 2019 (on average for one municipality)

The regional industry is dominated by local organizations of various sizes, a quarter of the large and medium-sized companies are controlled by holding companies such as Gazprom, Rosneft, Polyus, Ilim Group, Rosatom, Rostekh, Mechel, Renova, En+ Group, and RUSAL.

In recent years, as a result of the active development of oil and gas resources, the process of complex formation has begun 1 : for example, IOC is building a polymer plant in Ust-Kut (commissioning is planned in 2024) and is building the Ust-Kutsk gas processing plant for the supply of raw materials (to be launched in 2021).

RUSAL invested and attracted large investments in the construction of the Taishet aluminum plant (the launch was postponed to 2021), as well as the Taishet anode factory, which will meet the plant’s needs for baked anodes. The Ilim Group will build a pulp and cardboard mill in Ust-Ilimsk by 2023, which will increase the production of unbleached packaging materials. These and other projects, which were initiated by big business and are in an active stage, attract investments to the municipalities of the region ( Fig. 5 ).

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The share of investments in fixed assets of large and medium-sized organizations of Irkutsk oblast, %. Municipalities: 1 , Irkutsk; 2 , Katangsky district; 3 , Bratsk; 4 , Angarsk; 5 , Usolye-Sibirskoye; 6 , Ust-Kutsky district; 7 , Taishetsky district; 8 , others.

In 2010 the share of investments of the five leading municipalities in the region was 71.2%, while by 2019 the concentration increased to 78.8%. In 2017–2019 investment growth rates increased, on average, in most municipalities (85.7%), especially in municipalities of the third group, the Tulun, Ust-Ilimsky, Kuytunsky, and Cheremkhovsky districts. Per capita investment rates are the highest for municipalities of the first and second groups, Katangsky, Ust-Kutsky, and Bodaibinsky northern regions, which is explained by the large volumes of investments made by large companies in the development of natural resources and the low population density.

CONCLUSIONS

In the last decade, an increase in the share of the raw materials sector (by four times) with a significant decrease in the share of mechanical engineering (by four times), chemical production (by almost two times), energy, and metallurgy determines the structural shifts in the region’s economy. The shift towards the extractive sector, which is more focused on the export of raw materials, structurally simplifies the sectoral composition of industry.

The existing main territories for gold and iron ore mining (Bodaibinsky, Nizhneilimsky regions), as well as peripheral northern regions (Katangsky, Ust-Kutsky), areas for the development of oil and gas resources, have increased their importance and increased concentration in industrial production. In 2019, they accounted for the largest volume of shipped products in the extraction of minerals, 89.1% (2010, 50.6%). This is also facilitated by the pipeline system, the main ESPO oil pipeline and the Power of Siberia gas pipeline (its section under construction in the region), as well as the increased demand for hydrocarbons in the markets of the Asia–Pacific region. The development of the oil and gas industry attracted labor resources from other regions of the country (Western Siberia, the Republic of Tatarstan, etc.). In 2019, the number of workers on a rotational basis exceeded 25 000 people per quarter, of which more than 30% are residents of the region.

The cities, the leading industrial centers of the region (Bratsk, Irkutsk, Angarsk, Shelekhov, Ust-Ilimsk, and Sayansk), whose large enterprises were created in Soviet times, have adapted to changing conditions and still retain their stability. In 2019, they formed 87% of the shipped products of the manufacturing industry (in 2010, 90.5%). Other cities (Tulun, Zima, and Usolye-Sibirskoye) lost their importance as a result of the closure of city-forming enterprises in the post-Soviet period; in 2013, Baikalsk was added to them. As a regional center, Irkutsk is statistically attributed to a significant volume of shipped goods, works, and services in the energy sector (2019, 87.4%), which complicates the territorial analysis of this industry.

To identify intraregional differentiation of the level of industrial development in 2010 and 2019 four groups of medical organizations were identified, which are different in composition depending on the distribution of quantitative criteria (the share of people employed in industrial production and the volume of shipped products of large and medium-sized organizations). Six MOs changed their position in the groups, while the rest retained their positions,

Over the past 10 years, only five municipalities (Irkutsk, Bratsk, Angarsk, Katangsky, and Ust-Kutsky districts) have concentrated more than two-thirds of their investments in fixed assets, which indicates the extreme unevenness of their distribution. Basically, the resource advantages of the region in the implementation of large investment projects in gas chemistry, nonferrous metallurgy, timber processing, pulp and paper production, and mining are used by large businesses that control significant enterprises. However, investment activity has little effect on improving socioeconomic conditions, which has been noted by other researchers [ 14 , 21 ].

The work was carried out at the expense of the state assignment (АААА-А21-121012190019-9).

1 According to P.Ya. Baklanov, the processes of the initial formation and subsequent development of territorial combinations of nodal elements, various enterprises (or territorial-production complexes) are complex formation [ 20 , p. 213].

Contributor Information

N. A. Ippolitova, Email: ur.tsil@pi-anin .

M. A. Grigoryeva, Email: ur.xednay@9irgram .

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The Current Territorial Differentiation of the Industry of Irkutsk Oblast

M. A. Grigoryeva