Related Experiment Video
Updated: Oct 29, 2025
08:36
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
Published on: April 19, 2024
823
Data Analysis and Presentation in Integrative Reviews: A Narrative Review
Ahtisham Younas1,2, Sharoon Shahzad3, Shahzad Inayat4
1Faculty of Nursing, Memorial University of Newfoundland, St. John's, Canada.
Western Journal of Nursing Research
|July 12, 2021
Summary
This review analyzed data analysis and presentation methods in 151 integrative reviews. Most reviews lacked explicit methods or used inductive approaches, highlighting a need for clearer reporting in scientific literature.
Area of Science:
- Nursing Research
- Evidence Synthesis
Background:
- Integrative reviews are crucial for synthesizing evidence to inform clinical practice.
- Understanding the methodologies employed in these reviews is essential for ensuring rigor and reproducibility.
Approach:
- A systematic review of 151 integrative reviews published in nursing journals during 2019.
- Data extraction utilized summary tables, and synthesis employed a researcher-developed questions-based process.
- Data analysis and synthesis methods were categorized as non-specific, inductive, deductive, and framework-based.
Key Points:
- A significant number of integrative reviews (n=67) did not explicitly detail their data analysis and synthesis methods.
- Inductive methods were most commonly used (n=55), followed by deductive (n=13) and framework-based (n=13) approaches.
- While narrative descriptions were common for findings presentation, innovative methods like tables, concept maps, and word clouds were also utilized.
Conclusions:
- The study reveals considerable diversity in data analysis and presentation methods within integrative reviews.
- There is a notable lack of explicit methodological reporting in many integrative reviews, particularly concerning data analysis and synthesis.
- The adoption of varied presentation techniques, including innovative visual formats, can enhance the clarity and impact of review findings.
Related Concept Videos
01:13Review and Preview
10.1K
Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
10.1K
01:10Review and Preview
8.1K
In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
Percentiles are a type of fractile that partition data into...
8.1K
01:11Statistical Analysis: Overview
10.9K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
10.9K
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
213
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,...
213
01:12Analysis of Population Pharmacokinetic Data
477
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
477
01:20Biostatistics: Overview
431
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...
431