Development and validation of the SAFE (Socially Ascribed intersectional identities For Equity) questionnaire
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View abstract on PubMed
Summary
This summary is machine-generated.Researchers developed the Social and Intersectionality Framework for Evaluation (SAFE) questionnaire to capture how social perceptions impact individuals. This tool enhances intersectionality research by assessing complex social positions in large studies.
Area Of Science
- Social Sciences
- Sociology
- Public Health
Background
- Traditional surveys inadequately represent how social perceptions shape individual experiences and group categorization.
- Understanding perceived social positions is crucial for intersectionality research, as it influences negative impacts on individuals.
- Existing research highlights the complexity of social positions and their lived experiences.
Purpose Of The Study
- To develop and validate a novel questionnaire grounded in intersectionality theory and social position.
- To create a tool applicable to large-scale, population-based surveys and studies.
- To enhance the measurement of intersectional social dynamics in research.
Main Methods
- Synthesized data from 61 quantitative surveys and 197 qualitative studies on intersectionality.
- Developed a five-part draft questionnaire covering key identity and social status domains.
- Utilized an expert Delphi process for iterative refinement and validation of questionnaire items and response options.
Main Results
- A refined questionnaire, the Social and Intersectionality Framework for Evaluation (SAFE), was developed.
- The Delphi process achieved ≥75% consensus on questionnaire items and response options.
- The SAFE questionnaire demonstrates high relevance and accessibility for diverse populations.
Conclusions
- The SAFE questionnaire offers a significant advancement in understanding the intersectional nature of social participation and marginalization.
- This validated tool facilitates more nuanced research into social position and its effects.
- The SAFE questionnaire can be applied in large-scale studies to improve the measurement of intersectional experiences.
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