Related Experiment Video
Updated: Feb 23, 2026
05:02
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
33.9K
Using bibliometrics to support revalidation requirements
1National Council of State Boards of Nursing, Chicago, Illinois, United States.
Nursing Standard (Royal College of Nursing (Great Britain) : 1987)
|August 31, 2017
Summary
Bibliometrics offers nurse academics a way to document their professional development. This analysis of publications provides evidence for Nursing and Midwifery Council revalidation requirements.
Area of Science:
- Bibliometrics
- Nursing Research
- Academic Publishing
Background:
- Bibliometrics statistically analyzes academic works to assess research impact and productivity.
- Nurse academics need documented evidence for professional revalidation.
- The Nursing and Midwifery Council (NMC) has specific revalidation requirements.
Purpose of the Study:
- To explore the utility of bibliometrics for nurse academics.
- To demonstrate how bibliometric data can fulfill NMC revalidation requirements.
- To provide documented evidence of continuing professional development (CPD) for nurse academics.
Main Methods:
- Analysis of a single author's publication history using bibliographic software.
- Calculation of metrics such as h-index and citation counts.
- Thematic analysis of publications through co-word analysis, multidimensional scaling, and cluster analysis.
Main Results:
- Identified publication counts, journal distributions, and thematic clusters of academic work.
- Four key themes emerged: nursing and health policy, global influence, regulatory research, and leadership.
- Bibliometric data aligned with NMC revalidation criteria for CPD.
Conclusions:
- Bibliometrics is a suitable method for nurse academics to gather evidence for NMC revalidation.
- This approach offers a valid means for completing revalidation portfolios.
- Bibliometric analysis supports the demonstration of professional development and research impact.
Keywords:
Nursing and Midwifery Councilacademic publicationsbibliometricscontinuing professional developmenth-indexnurse academicsresearchrevalidationMore Related Videos
10:39Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
Published on: August 29, 2025
1.3K
07:50Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
Published on: April 18, 2025
1.1K
Related Concept Videos
01:03Data Validation
7.1K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Nursing assessment guides are generally based on holistic models rather than medical...
7.1K
01:15Data Validation
3.3K
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
Key parameters for method validation include:
3.3K
01:20Biostatistics: Overview
937
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Discrete variables are...
937
01:29Reliability and Validity
14.2K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
14.2K
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
500
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
500
01:16Critical Region, Critical Values and Significance Level
13.5K
The critical region, critical value, and significance level are interdependent concepts crucial in hypothesis testing.
In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the...
In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the...
13.5K