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Nursing Reports
Special Issues
Breakthroughs in Nursing: Clinical Reasoning and Decision-Making
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Breakthroughs in Nursing: Clinical Reasoning and Decision-Making

A special issue of Nursing Reports (ISSN 2039-4403).

Deadline for manuscript submissions: 30 May 2025 | Viewed by 968

Special Issue Editors

Prof. Dr. Márcia Pestana-Santos

E-Mail Website
Guest Editor
Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), 3000-076 Coimbra, Portugal
Interests: patient safety; clinical reasoning
Dr. Lara Daniela Matos Cunha

E-Mail Website
Guest Editor Assistant
Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), 3000-076 Coimbra, Portugal
Interests: clinical reasoning in complex healthcare settings; uncertainty associated with healthcare

Special Issue Information

Dear Colleagues,

Clinical reasoning is a crucial component of nursing practice, directly impacting patient outcomes and the quality of care. This Special Issue aims to explore the latest advancements, methodologies, and practical applications of clinical reasoning in nursing. We invite research articles, case studies, and reviews that address various aspects of clinical reasoning, including but not limited to diagnostic accuracy, critical thinking skills, the integration of evidence-based practice, and the use of simulation and technology in training. By examining diverse clinical settings and patient populations, this issue seeks to highlight innovative approaches and educational strategies that enhance nurses' decision-making abilities. Contributions that discuss the challenges and solutions in teaching clinical reasoning, as well as those that offer insights into interprofessional collaboration and its impact on clinical outcomes, are particularly welcome. This Special Issue will serve as a valuable resource for educators, practitioners, and policymakers aiming to improve clinical reasoning skills and, ultimately, patient care quality in nursing.

We are pleased to invite you to contribute to our upcoming Special Issue, "Breakthroughs in Nursing: Clinical Reasoning and Decision-Making". This issue aims to gather cutting-edge research, insightful case studies, and comprehensive reviews that delve into the various dimensions of clinical reasoning and decision-making in nursing. This Special Issue aligns with Nursing Reports' commitment to advancing nursing practice through evidence-based research and education, covering clinical practice and healthcare policy to ensure broad relevance across nursing science.

In this Special Issue, we welcome a variety of article types, including original research articles and reviews. We encourage submissions that cover, but are not limited to, the following themes:

  1. Diagnostic Accuracy:
    • Studies on methods and strategies to improve diagnostic accuracy in nursing practice.
    • Analysis of factors influencing diagnostic decision-making.
  2. Critical Thinking Skills:
    • Research on the development and assessment of critical thinking skills in nursing education and practice.
    • Innovative teaching methods to enhance critical thinking abilities.
  3. Integration of Evidence-Based Practice:
    • Implementation and impact of evidence-based practice on clinical reasoning.
    • Case studies demonstrating the successful integration of evidence into clinical decision-making.
  4. Use of Simulation and Technology in Training:
    • Role of simulation-based learning in improving clinical reasoning skills.
    • Advances in technology and their application in nursing education and practice.
  5. Innovative Approaches and Educational Strategies:
    • Novel educational interventions aimed at enhancing clinical reasoning.
    • Evaluation of educational programs and their effectiveness in fostering clinical reasoning.
  6. Challenges and Solutions in Teaching Clinical Reasoning:
    • Exploration of barriers to teaching clinical reasoning in nursing education.
    • Effective strategies and solutions to overcome these challenges.
  7. Interprofessional Collaboration:
    • Impact of interprofessional teamwork on clinical reasoning and patient outcomes.
    • Case studies and research on collaborative approaches to clinical decision-making.
  8. Artificial Intelligence (AI) in Clinical Reasoning:
    • The role of AI in enhancing clinical reasoning and decision-making in nursing.
    • Research on AI-driven tools and technologies that support clinical reasoning.
    • Case studies and reviews on the integration of AI in clinical practice and nursing education.

We look forward to receiving insightful contributions to this Special Issue. Your research and insights will be fundamental in advancing the field of clinical reasoning in nursing, ultimately leading to improved patient care and outcomes.

Prof. Dr. Márcia Pestana-Santos
Guest Editor

Dr. Lara Daniela Matos Cunha
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Nursing Reports is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • clinical reasoning
  • clinical decision-making
  • clinical judgment
  • critical thinking
  • evidence-based nursing

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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14 pages, 241 KiB  
Article
Steps to Adapt the Medication Administration Error Survey in Highly Specialised Units—Polish Perspectives
by Katarzyna Kwiecień-Jaguś, Wioletta Mędrzycka-Dąbrowska and Monika Kopeć
Nurs. Rep. 2025, 15(5), 173; https://doi.org/10.3390/nursrep15050173 - 14 May 2025
Viewed by 177
Abstract
Background and Objectives: Medication errors are a critical issue in healthcare systems worldwide, contributing to significant patient harm, with studies indicating that medication-related incidents are among the most common causes of adverse events in medical practice. There are between 80 and 200 steps [...] Read more.
Background and Objectives: Medication errors are a critical issue in healthcare systems worldwide, contributing to significant patient harm, with studies indicating that medication-related incidents are among the most common causes of adverse events in medical practice. There are between 80 and 200 steps in providing a single patient with a single dose of drugs, with five stages, including prescription, preparation, dispensation, administration and monitoring. This study aims to describe and validate the MAEs (Medication Administration Error Scale) tool, which investigates the most common causes of medication errors in medication administration. Materials and Methods: Independent translators translated the original version of the scale using language verification. The agreed-upon version of the translation was then assessed by a team of nurses, specialists in anaesthetic and intensive care nursing, in terms of understanding the translated content. After introducing changes resulting from linguistic and organisational differences, a survey questionnaire was prepared and used in the pilot study. Eighty-six respondents participated in the pilot study via the Office 365 platform and the Forms programme. The research was led by nurses who work in highly specialised units. The reliability of the translated version of the questionnaire was examined by calculating the Cronbach’s alpha coefficient. Results: The tool’s internal consistency across ranges was within acceptable limits. For part A (questions 1–29), it was 0.93; for part B (questions 30–45), it was 0.94. In part C, regarding the percentages of the type of error occurring in a given medical facility, Cronbach’s alpha coefficient was 0.97. When the factor loadings of the items were evaluated, they were determined to be in the range of 0.602–0.783. In this context, the factor loading levels of the items in the 5-factor model were high and sufficient. Conclusions: The statistical analyses suggest that the Polish version of the Medication Administration Error Survey demonstrates satisfactory reliability and is a promising tool for assessing the cause of medication administration errors. Full article
(This article belongs to the Special Issue Breakthroughs in Nursing: Clinical Reasoning and Decision-Making)
18 pages, 642 KiB  
Article
Satisfaction and Self-Confidence of Moroccan Nursing Students in Simulation-Based Learning and Their Associations with Simulation Design Characteristics and Educational Practices
by Hicham Blaak, Abdelmajid Lkoul, Hayat Iziki, Abdelhadi El Haddaouy, Ahmed Kharabch, Rachid Razine, Lahcen Belyamani and Majdouline Obtel
Nurs. Rep. 2025, 15(5), 138; https://doi.org/10.3390/nursrep15050138 - 25 Apr 2025
Viewed by 307
Abstract
Background: Nursing students must be able to enter clinical practice as safe, accurate, competent, and compassionate professionals. Objectives: The aim of this study was to investigate the effectiveness of simulation training on the satisfaction and self-confidence of undergraduate nursing students. Methods: A [...] Read more.
Background: Nursing students must be able to enter clinical practice as safe, accurate, competent, and compassionate professionals. Objectives: The aim of this study was to investigate the effectiveness of simulation training on the satisfaction and self-confidence of undergraduate nursing students. Methods: A cross-sectional and correlational study was conducted among 151 students enrolled in the third semester of nursing. Data were collected using a questionnaire comprising three instruments: SSSCL, SDS, and EPQ. Pearson’s correlation analysis was used to examine the relationship between satisfaction and self-confidence. Multiple linear regression was conducted to assess the influence of simulation design and various educational practices on students’ satisfaction and self-confidence. Results: The results revealed high mean scores for satisfaction (4.41 ± 0.40) and self-confidence (4.50 ± 0.36). A moderate, significant positive correlation was found between self-confidence and satisfaction (r = 0.579, p < 0.001). Furthermore, various learning methods (B = 0.112, p = 0.037, 95% CI [0.007; 0.217]) and objectives/information clarity (B = 0.175, p = 0.040, 95% CI [0.008; 0.342]) had a significant positive effect on satisfaction. Similarly, active learning (B = 0.146, p = 0.020, 95% CI [0.023; 0.268]) and feedback (B = 0.154, p = 0.035, 95% CI [0.011; 0.297]) had a significant positive effect on self-confidence. Conclusions: This study confirms that simulation-based training effectively boosts nursing students’ satisfaction and self-confidence, supporting its integration as a key component of nursing education to better prepare them for clinical challenges. Full article
(This article belongs to the Special Issue Breakthroughs in Nursing: Clinical Reasoning and Decision-Making)
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19 pages, 2589 KiB  
Systematic Review
Critical Thinking and Clinical Decision Making Among Registered Nurses in Clinical Practice: A Systematic Review and Meta-Analysis
by Nur Hidayah Zainal, Md Asiful Islam, Nur Syahmina Rasudin, Zakira Mamat, Tengku Muhammad Hanis, Wan Shakira Rodzlan Hasani and Kamarul Imran Musa
Nurs. Rep. 2025, 15(5), 175; https://doi.org/10.3390/nursrep15050175 - 20 May 2025
Abstract
Background: Critical thinking is fundamental for registered nurses (RNs) when making clinical decisions, which impact patient outcomes. This review aimed to identify studies on critical thinking and clinical decision making among nurses in clinical practice and synthesize their findings based on the regional [...] Read more.
Background: Critical thinking is fundamental for registered nurses (RNs) when making clinical decisions, which impact patient outcomes. This review aimed to identify studies on critical thinking and clinical decision making among nurses in clinical practice and synthesize their findings based on the regional area, observed findings, and predictive factors, and to assess the measurement tools used. Methods: A comprehensive search of the PubMed, Web of Science, CINAHL, and SCOPUS databases up to December 2024 was conducted in accordance with the PRISMA guidelines. The Newcastle–Ottawa Scale was used to assess the quality of included studies. Studies with similarly themed components were grouped for narrative synthesis. A meta-analysis of random-effects model calculations was performed. Results: This review included forty studies (twenty-four on CT, twelve on CDM, four on both) from various WHO regions, revealing diverse findings on observed skills. Ten CT and four CDM measurement tools were identified. Many studies also explored individual and group-level predictive factors for these skills. Meta-analyses of four common tools (CCTDI, NCT4P, CDMNS, and NDMI) showed significant heterogeneity, with statistically significant pooled mean scores. Conclusions: The synthesis highlights the global research on nurses’ critical thinking and clinical decision making, including the exploration of various predictive factors. However, the significant heterogeneity in the findings from meta-analyses of commonly used measurement tools underscores a need for more standardized measurement and analytical approaches, such as multilevel modeling, to better account for the hierarchical nature of potential predictive factors (individual and group levels), which would allow for more reliable comparisons and stronger conclusions in this field. Full article
(This article belongs to the Special Issue Breakthroughs in Nursing: Clinical Reasoning and Decision-Making)
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