Quality Appraisal Tools for Quantitative, Qualitative, and Mixed-Methods Studies: A Review and a Brief New Checklist

Purpose Existing research quality appraisal tools in the social sciences face significant disciplinary incompatibility and methodological limitations. This study aims to address these gaps by evaluating current tools and developing a versatile new checklist to standardize quality assessment across quantitative, qualitative, and mixed-methods studies. Design/Approach/Methods A systematic literature analysis of 24 mainstream appraisal tools assessed their disciplinary compatibility, methodological scope, and criteria design. A new checklist (i.e., Quantitative, Qualitative, and Mixed-Methods Studies [QQM] checklist) was developed using a utility-usability framework, integrating common indicators to ensure methodological inclusiveness for studies. Findings Analysis revealed most tools are restricted to single methods, 67% focus on medical fields, and only two are discipline-specific for social sciences. Issues of existing tools include ambiguous criteria, rigid binary scoring, and outdated frameworks. The QQM checklist addresses these gaps with eight universal indicators and method-specific criteria (4–6 for quantitative, 6 for qualitative), using a three-tiered scoring system (0–2 points). Originality/Value The QQM checklist offers a standardized solution for quality appraisal in social sciences, transcending disciplinary and methodological boundaries. Its design enables AI integration, advancing standardization for consistent, rigorous evaluations—critical for funding, publication, and policy decisions. This work contributes to improving research quality and transparency in the social sciences.

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Publication Details

Journal
ECNU Review of Education
Published
2025-09-01
DOI
https://doi.org/10.1177/20965311251371227
Citations
5
Primary Topic
Evaluation and Performance Assessment
Type
article
Field-Weighted Citation Impact
10.53
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article

Quality Appraisal Tools for Quantitative, Qualitative, and Mixed-Methods Studies: A Review and a Brief New Checklist

Jennifer Symonds, Zixin Zeng, Xin Tang, Haoyan Huang
5 citations
ECNU Review of Education
Evaluation and Performance Assessment
10.53
article

Quality Appraisal Tools for Quantitative, Qualitative, and Mixed-Methods Studies: A Review and a Brief New Checklist

Jennifer Symonds, Zixin Zeng, Xin Tang, Haoyan Huang
article en
5 citations

Abstract

Purpose Existing research quality appraisal tools in the social sciences face significant disciplinary incompatibility and methodological limitations. This study aims to address these gaps by evaluating current tools and developing a versatile new checklist to standardize quality assessment across quantitative, qualitative, and mixed-methods studies. Design/Approach/Methods A systematic literature analysis of 24 mainstream appraisal tools assessed their disciplinary compatibility, methodological scope, and criteria design. A new checklist (i.e., Quantitative, Qualitative, and Mixed-Methods Studies [QQM] checklist) was developed using a utility-usability framework, integrating common indicators to ensure methodological inclusiveness for studies. Findings Analysis revealed most tools are restricted to single methods, 67% focus on medical fields, and only two are discipline-specific for social sciences. Issues of existing tools include ambiguous criteria, rigid binary scoring, and outdated frameworks. The QQM checklist addresses these gaps with eight universal indicators and method-specific criteria (4–6 for quantitative, 6 for qualitative), using a three-tiered scoring system (0–2 points). Originality/Value The QQM checklist offers a standardized solution for quality appraisal in social sciences, transcending disciplinary and methodological boundaries. Its design enables AI integration, advancing standardization for consistent, rigorous evaluations—critical for funding, publication, and policy decisions. This work contributes to improving research quality and transparency in the social sciences.

ECNU Review of Education
University of Helsinki (FI), Shanghai Jiao Tong University (CN), University College London (GB), University of Hong Kong (HK)
Openalex Percentile: Top 2%
Evaluation and Performance Assessment
10.53
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