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This is a peer-review report for “Estimating Variance of Log Standardized Incidence Ratios Assessing Health Care Providers’ Performance: Comparative Analysis Using Bayesian, Bootstrap, and Delta Method Approaches.”
JMIRx Med 2025;6:e83798
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This is the authors’ response to the peer-review report of “Estimating Variance of Log Standardized Incidence Ratios Assessing Health Care Providers’ Performance: Comparative Analysis Using Bayesian, Bootstrap, and Delta Method Approaches.”
JMIRx Med 2025;6:e83796
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Although funnel plots have been used in meta-analyses, in particular to detect publication bias, they have recently been strongly recommended as the most appropriate way to display performance indicators such as comparisons of risk-adjusted rates between health care units [8]. SMRs are the commonly used performance index for institutional comparisons [9].
JMIRx Med 2025;6:e77415
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Some variations between the average F1-score performance differences were observed (see Figure 3).
Our results show that more advanced models outperform less advanced ones. The largest difference between the category performance F1-scores was observed between the BT category and the rule-based category. BT models were compared with rule-based models in 4 studies, yielding an average performance difference of 0.2335 in terms of F1-score. BT was the best-performing category.
JMIR Med Inform 2025;13:e68707
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In an evaluation of the performance of the original National Early Warning Score (NEWS), it demonstrated consistent predictive accuracy across multiple patient groups [5]. However, the performance of NEWS2 varies between care settings and between patients with different characteristics [11,16,17].
JMIR Res Protoc 2025;14:e70303
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If a study demonstrated statistical significance for a particular outcome (any related outcome indicators in physical, cognitive, or dual-task performance), it was considered valid in that area (eg, physical, cognitive, or dual-task performance). In these cases, if there are some outcome indicators with statistical significance, they were marked with a checkmark.
The literature search yielded 5874 potentially relevant studies.
JMIR Serious Games 2025;13:e67250
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A Practical Guide and Assessment on Using ChatGPT to Conduct Grounded Theory: Tutorial
Reliability is a key metric for evaluating Chat GPT’s coding performance, assessing whether different coders (human or machine) produce similar results [9-11]. Typical measures include percent agreement (comparing human and artificial intelligence [AI] coding similarity) and the κ coefficient (measuring agreement beyond chance) [12,13].
J Med Internet Res 2025;27:e70122
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Recent studies have extensively evaluated the performance of generative AI models in medical question-answering scenarios. These models have shown promising results in medical licensing examinations [4,5] clinical case discussions and diagnostic reasoning [6,7]. However, their performance varies significantly based on task complexity.
JMIR AI 2025;4:e66796
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The Applications of Large Language Models in Mental Health: Scoping Review
When evaluating the performance of these LLMs, most studies measured the performance of LLMs with various metrics, such as F1-score (54/95, 57%), precision (34/95, 36%), accuracy (45/95, 47%), and recall (32/95, 34%).
The number of studies mapped by country is presented in Figure 3 A (a higher resolution version of figure is also available in Multimedia Appendix 5).
J Med Internet Res 2025;27:e69284
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Thus, in this context it should be considered regarding the corresponding perceived performance and frustration when performing the task. Positive mental effort should be accompanied by high perceived performance and low frustration. To make the notion of positive mental effort operational, we return to the definition of this concept, specifying that it is part of the MWL construct.
JMIR Form Res 2025;9:e63491
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