Tools to assist in study quality assessment

Assessing the quality of studies is a critical step in evidence-based practice, systematic reviews, and meta-analyses.

High-quality studies provide reliable evidence for clinical and public health decision-making, while low-quality studies can introduce bias and distort findings.

Several tools are available to assist researchers, clinicians, and reviewers in evaluating study quality effectively.

Risk of Bias Tools

a. Cochrane Risk of Bias Tool (RoB 2)

The Cochrane Risk of Bias Tool is specifically designed for randomised controlled trials (RCTs). The latest version, RoB 2, evaluates five domains:

• Bias arising from the randomization process

• Bias due to deviations from intended interventions

• Bias due to missing outcome data

• Bias in measurement of the outcome

• Bias in selection of the reported result

b. ROBINS-I (Risk of Bias in Non-Randomised Studies of Interventions)

ROBINS-I is designed for non-randomised studies. It assesses bias in seven domains, including confounding, participant selection, and outcome measurement.

Statistical tools

a. RevMan (Review Manager)

RevMan (Review Manager) is a software developed by the Cochrane Collaboration to support the preparation and analysis of systematic reviews and meta-analyses, particularly in healthcare. It facilitates protocol development, data management, risk of bias assessment, and statistical analyses, including meta-analyses using fixed-effect or random-effects models. It integrates risk of bias tools like RoB 2 and provides visual outputs.

RevMan also generates visual outputs like forest plots and funnel plots, helping researchers present and interpret their findings. With a user-friendly interface and templates for systematic review sections, RevMan ensures consistency and adherence to Cochrane standards.

Available as both desktop software and an online version (RevMan Web), it is widely used by researchers for its comprehensive tools and free accessibility, though it has limitations for advanced statistical methods compared to software like R or STATA.

b. Excel

Microsoft Excel is a versatile tool that can be used to create risk-of-bias graphs and summaries in systematic reviews. Researchers can use Excel to input, organise, and visualise the risk of bias data for each study included in the review.

Customizable features, such as tables and conditional formatting, allow users to present detailed summaries of bias across domains (e.g., selection bias, performance bias, detection bias) with clear colour coding (e.g., red for high risk, yellow for unclear risk, and green for low risk).

Excel’s flexibility and ease of use make it a practical option for researchers, even though it lacks the automation and specific functionalities available in dedicated systematic review software like RevMan.