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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.

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

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|March 9, 2026
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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.