SCoRE-Layer: a structured method for relational analysis of results in scoping reviews.

INTRODUCTION: Scoping reviews are widely used to map the extent of the available literature and to organize the main concepts that structure a given topic. However, their results are usually presented as descriptive categories, with limited emphasis on how these dimensions appear together and how these combinations are distributed across the evidence base. OBJECTIVE: The objective of this study is to develop and evaluate the feasibility of the SCoRE-Layer, a structured analytical method designed to represent the relational architecture of evidence in scoping reviews through co-occurrence matrices and descriptive structural metrics. METHODS: This methodological study focused on the conceptual development, mathematical formalization, and operational structuring of SCoRE-Layer. To avoid conflating development and implementation, method development followed four analytical movements, whereas method implementation was organized into five interdependent operational stages: construction of a structured categorical system; independent coding allowing multiple categories per study; development of co-occurrence matrices between analytical dimensions; application of descriptive structural metrics associated with classification based on predefined cut-off points; and systematic identification of structural gaps based on the comparison between expectation and observation. The internal coherence and operational feasibility of the proposed method were examined through demonstrative application in three illustrative datasets. RESULTS: The SCoRE-Layer made explicit the combinations between categories, quantified the connectivity of the investigated field, differentiated recurrence from relational specificity, classified structural patterns, and systematically identified gaps, while preserving the inherently descriptive nature of scoping reviews. The method also supported a more structured interpretation of how evidence is distributed across analytical dimensions, including in implementation-oriented readings of the literature. CONCLUSION: The method enhances the analytical capacity of scoping reviews by explicitly modeling the relational organization of evidence without exceeding their interpretative boundaries. In addition, it broadens the practical interpretability of mapped evidence by supporting clearer identification of central patterns, peripheral configurations, and underexplored gaps, including in implementation-oriented evidence syntheses. SPANISH ABSTRACT: https://links.lww.com/IJEBH/A709.

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PubMed
Published
2026-10-08
DOI
https://doi.org/10.1097/xeb.0000000000000661
Primary Topic
Meta-analysis and systematic reviews
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article
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article

SCoRE-Layer: a structured method for relational analysis of results in scoping reviews.

Tahissa Frota Cavalcante, Francisco Bahia Pena, José Erivelton de Souza Maciel Ferreira
PubMed
Meta-analysis and systematic reviews
article

SCoRE-Layer: a structured method for relational analysis of results in scoping reviews.

Tahissa Frota Cavalcante, Francisco Bahia Pena, José Erivelton de Souza Maciel Ferreira
article en

Abstract

INTRODUCTION: Scoping reviews are widely used to map the extent of the available literature and to organize the main concepts that structure a given topic. However, their results are usually presented as descriptive categories, with limited emphasis on how these dimensions appear together and how these combinations are distributed across the evidence base. OBJECTIVE: The objective of this study is to develop and evaluate the feasibility of the SCoRE-Layer, a structured analytical method designed to represent the relational architecture of evidence in scoping reviews through co-occurrence matrices and descriptive structural metrics. METHODS: This methodological study focused on the conceptual development, mathematical formalization, and operational structuring of SCoRE-Layer. To avoid conflating development and implementation, method development followed four analytical movements, whereas method implementation was organized into five interdependent operational stages: construction of a structured categorical system; independent coding allowing multiple categories per study; development of co-occurrence matrices between analytical dimensions; application of descriptive structural metrics associated with classification based on predefined cut-off points; and systematic identification of structural gaps based on the comparison between expectation and observation. The internal coherence and operational feasibility of the proposed method were examined through demonstrative application in three illustrative datasets. RESULTS: The SCoRE-Layer made explicit the combinations between categories, quantified the connectivity of the investigated field, differentiated recurrence from relational specificity, classified structural patterns, and systematically identified gaps, while preserving the inherently descriptive nature of scoping reviews. The method also supported a more structured interpretation of how evidence is distributed across analytical dimensions, including in implementation-oriented readings of the literature. CONCLUSION: The method enhances the analytical capacity of scoping reviews by explicitly modeling the relational organization of evidence without exceeding their interpretative boundaries. In addition, it broadens the practical interpretability of mapped evidence by supporting clearer identification of central patterns, peripheral configurations, and underexplored gaps, including in implementation-oriented evidence syntheses. SPANISH ABSTRACT: https://links.lww.com/IJEBH/A709.

PubMed
Universidade Federal de Ouro Preto (BR), University for International Integration of the Afro-Brazilian Lusophony (BR)
Openalex Percentile: Top 10%
Meta-analysis and systematic reviews
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