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Updated: Mar 11, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Quality assessment reporting checklists for microsimulation models: A scoping review protocol.

Claire de Oliveira1,2,3,4,5

  • 1Institute for Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.

Plos One
|March 9, 2026
PubMed
Summary

Formal reporting checklists are needed to evaluate microsimulation models. This scoping review will synthesize existing literature on quality assessment and best practices for these important economic models.

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Area of Science:

  • Computational Social Science
  • Economic Modeling
  • Policy Analysis

Background:

  • Microsimulation models are crucial for understanding economic agent behavior and informing government policy decisions.
  • Ensuring the quality and usefulness of these models is paramount for reliable insights.
  • Currently, no formal reporting checklists exist to evaluate the quality of microsimulation models.

Purpose of the Study:

  • To conduct a scoping review to identify and synthesize existing literature on quality assessment checklists for microsimulation models.
  • To gather information on best practices, guidelines, and recommendations for developing robust microsimulation models.
  • To address the absence of formal quality assessment tools for microsimulation models.

Main Methods:

  • The study will employ a scoping review methodology adhering to PRISMA guidelines for Scoping Reviews.
  • Comprehensive literature searches will be conducted across multiple databases (MEDLINE, Embase, EconLit, Web of Science) and supplemented with targeted web and journal searches.
  • Data extraction will focus on quality dimensions, followed by a narrative synthesis to summarize recommendations.

Main Results:

  • Preliminary assessment indicates a lack of formal checklists for evaluating microsimulation model quality.
  • No prior scoping reviews have specifically addressed this topic.
  • The review will identify and synthesize any existing recommendations for developing high-quality microsimulation models.

Conclusions:

  • There is a significant gap in the literature regarding formal quality assessment tools for microsimulation models.
  • This work will consolidate existing knowledge on best practices for developing robust microsimulation models.
  • The development of a validated quality assessment reporting checklist is anticipated as a key outcome, filling a critical need in the field.