Meta Analysis Nursing Literature Meta-analysis is a powerful tool in nursing research that enables the synthesis of data from multiple studies to derive more comprehensive and reliable conclusions. This method has significantly contributed to evidence-based practice by integrating findings across various studies and resolving inconsistencies in the literature.
What is Meta-Analysis?
Meta-analysis is a quantitative approach that allows the synthesis and integration of results from multiple individual studies addressing a specific research question. First introduced by Glass in 1976, meta-analysis is described as an “analysis of analyses.” Unlike traditional narrative reviews, it involves a systematic research process where individual studies are treated as the sample. Findings from each study are transformed into a common metric known as an effect size, which measures the magnitude of the experimental effect on outcome variables.
Experimental and Control Groups
In meta-analysis, once the results from each study have been converted to a common metric, they can be pooled together for synthesis. The most common effect size indicators are:
- r: The Pearson product-moment correlation coefficient.
- d index: Cohen’s d, which represents the difference between the means of the experimental and control groups, divided by the standard deviation.
Cohen (1988) provided guidelines for interpreting the magnitude of these effect sizes:
- r:
- Small: 0.10
- Medium: 0.30
- Large: 0.50 or more
- d:
- Small: 0.2
- Medium: 0.5
- Large: 0.8 or more
Approaches for Meta-Analysis
Several approaches are available to reduce bias and enhance the reliability of a meta-analysis:
- Publication Bias: A common bias in meta-analysis is the tendency to publish positive results over negative ones. This can skew the findings.
- Weighting of Studies: Studies included in a meta-analysis should not necessarily be given equal weight. Differences in sample size, quality, and methodology should be considered.
- Inclusion of Multiple Tests: Care must be taken to avoid including multiple tests of the same hypothesis from a single study without adjusting for non-independence.
- File Drawer Problem: This refers to the potential existence of unpublished studies with nonsignificant results that, if included, might alter the meta-analysis findings. Rosenthal (1979) developed a technique to estimate the number of unpublished studies required to change the conclusions of a meta-analysis.
Meta-Analysis and Sample Size
Not all studies synthesized in a meta-analysis should be given equal weight. Some studies may have small, unrepresentative samples or poor design, while others may use randomized control group designs with large sample sizes. To address this:
- Quality Scoring: Studies can be evaluated and assigned a quality score, and meta-analyses can be weighted accordingly.
Non-Independence and Its Sources
Non-independence in a meta-analysis can occur when multiple hypothesis tests are based on several variables measured within a single study. One remedy for this is to combine these findings into a single, global hypothesis test to avoid bias from non-independent data points (Strube & Hartman, 1983).
Specific Assumptions
Before combining specific studies in a meta-analysis, certain assumptions should be met:
- Representativeness: Each study should provide sample estimates of effect sizes representative of the population effect size.
- Homogeneity Tests: These tests can identify outlier studies. If outliers are detected, they may be removed to prevent distortion of the meta-analysis results.
Meta-Analysis in Nursing Literature
Meta-analysis first appeared in nursing literature in 1982, when O’Flynn published an article in the “Methodology Corner of Nursing Research.” A meta-analysis on the effects of psychoeducational interventions on the length of post-surgical hospital stays (Devine & Cook, 1983) was the first of its kind published in nursing.
Since then, meta-analyses have been conducted in various areas, such as:
- Patient outcomes for nurse practitioners and nurse-midwives.
- Job satisfaction and turnover among nurses.
- The relationship between postpartum depression and maternal-infant interaction.
- Effects of educational interventions in diabetes care.
- Quality of life in cardiac patients.
- Benefits of non-nutritive sucking in preterm infants.
For instance, a meta-analysis by Beck (1996) on predictors of postpartum depression integrated findings from 44 studies, clarifying significant predictors such as prenatal depression, previous depression, social support, life stress, childcare stress, maternity blues, marital satisfaction, and prenatal anxiety. An instrument based on these findings can help detect women at risk for postpartum depression.
Benefits of Meta-Analysis in Nursing Research
Meta-analysis offers several benefits to nursing research:
- Knowledge Development: Meta-analysis helps further knowledge development by integrating findings from multiple studies, providing a clearer understanding of complex issues.
- Evidence-Based Practice: It supports evidence-based nursing practice by synthesizing data to inform clinical decision-making. Nurses can decide whether to apply research findings based on the size of the difference an intervention makes.
- Resolving Conflicting Findings: Meta-analysis can resolve issues in nursing research where multiple studies report conflicting findings. By pooling data, meta-analysis helps provide more definitive conclusions.
- Identifying Research Gaps: Meta-analysis highlights gaps in nursing research, identifying areas where further studies are needed.
- Improving Practice Outcomes: Meta-analysis can have direct consequences on nursing practice by clarifying which interventions are most effective and should be adopted widely.
Conclusion
Meta-analysis is a robust quantitative tool that significantly enhances nursing research by providing a more rigorous and systematic synthesis of study results. It aids in resolving conflicting evidence, advancing nursing knowledge, guiding evidence-based practice, and identifying areas for future research. By applying meta-analysis, nursing researchers can provide more definitive answers to critical questions, ultimately improving patient care outcomes and the effectiveness of nursing interventions.