Work

EQUALSS GUIDE Multiple: A novel framework for equity-focused evidence synthesis

Year: 2025

Type: article

Abstract: Background: Understanding the differential effects of health and care interventions across disadvantaged groups is essential in addressing inequalities and avoiding inadvertently worsening them. Previous research has highlighted limitations with the existing PROGRESS-Plus framework. We aimed to develop a framework to allow researchers to synthesise evidence with an equity perspective. Methods: First, we re-analysed articles from the EQUALISE study, a review of interventions that increase or decrease inequalities in general practice, to explore the various domains of disadvantage examined in the included studies. We then compared these domains of disadvantage with the existing PROGRESS-Plus framework. Finally, we propose a new framework to support equity-focused evidence synthesis. Findings: From the 325 studies included in EQUALISE, the most commonly assessed PROGRESS-Plus domains were sex/gender (53%), ethnicity/race (50%), and age (44%). The PROGRESS-Plus framework did not include explict mention of context-specific groups, those with multiple intersecting disadvantage, and people who experience disability. Building on PROGRESS-Plus, our new framework EQUALSS GUIDE Multiple includes: Ethnicity and race, Qualifications and education, Underserved area, Age, Language and religion, Sex, Sexual orientation, Gender identification, Underrepresented groups (inclusion groups), Income and wealth, Disability (physical, mental and learning), Employment and occupation, and Multiple disadvantage. Interpretation: EQUALSS GUIDE Multiple builds on PROGRESS-Plus to encapsulate key domains of disadvantage while allowing for context-specific flexibility. Examining the effectiveness of policy and practice interventions by disadvantaged groups is paramount to prioritise actions that narrow the health gap and prevent actions which widen inequalities.

Source: Public Health in Practice

DOI: 10.1016/j.puhip.2025.100600

Authors: Lucy McCann, Lucy Johnson, Anna Gkiouleka, Helen Pearce, John Ford

Institution: Queen Mary University of London

Language: English

Topic: Meta-analysis and systematic reviews

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

SDGs: Reduced inequalities, Good health and well-being

Open Access status: gold

Estimated APC paid: $2,060