Exploring evaluation measures of large language models for family caregiver use: A scoping review

This review provides a comprehensive overview of the measures for evaluating large language models and highlights the need for their improvement using reliable and valid measures. The findings guide the direction of future research and practice to maximize the benefits through continuous quality improvement.

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Publication Details

Journal
Digital Health
Published
2026-02-01
DOI
https://doi.org/10.1177/20552076261425343
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploring evaluation measures of large language models for family caregiver use: A scoping review

Gregory L. Alexander, Hannah Cho, Han Soojeong, Yong K Choi
Digital Health
Artificial Intelligence in Healthcare and Education
article

Exploring evaluation measures of large language models for family caregiver use: A scoping review

Gregory L. Alexander, Hannah Cho, Han Soojeong, Yong K Choi
article en

Abstract

This review provides a comprehensive overview of the measures for evaluating large language models and highlights the need for their improvement using reliable and valid measures. The findings guide the direction of future research and practice to maximize the benefits through continuous quality improvement.

Digital HealthVol. 12
University of Pittsburgh (US), Columbia University (US), University of Pennsylvania (US)
Quality Education
Openalex Percentile: Top 53%
Artificial Intelligence in Healthcare and Education
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