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COVID-19 后神经科学与神经药理学杂志文献计量指标的弹性与重新校准:使用混合效应模型的纵向变化率分析

Resilience and Recalibration of Bibliometric Indicators in Neurosciences and Neuropharmacology Journals After COVID-19: A Longitudinal Rate of Change Analysis Using Mixed-Effects Models.

作者信息

Rios-Castañeda Camilo, Aguirre-Meneses Heriberto, Nuñez-Gaona Marco-Antonio, Roldan-Valadez Ernesto

机构信息

Division of Neurosciences, Instituto Nacional de Rehabilitacion 'Luis Guillermo Ibarra Ibarra', 14389, Mexico City, Mexico.

Department of Medical Systems, Instituto Nacional de Rehabilitacion 'Luis Guillermo Ibarra Ibarra', 14389, Mexico City, Mexico.

出版信息

Curr Neuropharmacol. 2025 Jul 21. doi: 10.2174/011570159X384613250702110845.

DOI:10.2174/011570159X384613250702110845
PMID:40696548
Abstract

INTRODUCTION

The COVID-19 pandemic triggered unprecedented changes in the scholarly publishing landscape, particularly in biomedical fields such as Neurosciences and Neuropharmacology. Several journals experienced steep, short-term increases in citation metrics during 2020-2022. However, it remains uncertain whether these surges reflected a sustainable impact or temporary inflation. This study aimed to analyze post-pandemic bibliometric behavior by evaluating the Rate of Change (RoC) in key journal-level indicators from 2013 to 2023.

METHODS

A retrospective longitudinal study was conducted on 233 neuroscience journals indexed in the Journal Citation Reports. Six indicators were analyzed: Journal Impact Factor (JIF), Eigenfactor Score, Immediacy Index, Article Influence Score, Cited Half-Life, and Total Citations. RoC was calculated for each metric on an annual basis. Mixed-effects models with random intercepts and slopes were constructed to evaluate longitudinal trajectories and identify changes associated with three defined periods: prepandemic (2013-2019), pandemic (2020-2022), and post-pandemic (2023). Subgroup analyses assessed journal quartiles and categories to explore variations in impact resilience.

RESULTS

The pandemic period (2020-2022) showed significant increases in RoC for JIF (mean β = +4.85, p = 0.004), Immediacy Index (β = +6.22, p = 0.002), and Total Citations (β = +5.88, p < 0.001). These changes were more prominent in top-quartile journals and those classified under Neuropharmacology. In contrast, alternative metrics such as the Eigenfactor Score and Article Influence Score remained relatively stable across the same period. In 2023, most indicators exhibited a normalization trend, with JIF and Immediacy Index showing marked deceleration in RoC, suggesting a post-pandemic recalibration. Journals with sustained positive trajectories were primarily concentrated in high-impact clusters, with Current Neuropharmacology ranking among the top performers by RoC slope.

DISCUSSION

The findings demonstrate that the surge in citations during the pandemic was primarily transitory and varied across bibliometric indicators. Traditional metrics like JIF and Immediacy Index were more sensitive to systemic shocks, while influence-based indicators (Eigenfactor and Article Influence Score) showed higher temporal resilience. The application of RoC allowed for a nuanced interpretation of metric trajectories and minimized misinterpretation of short-term spikes. Limitations include reliance on publicly available data and potential lag effects in citation behavior not fully captured within the 10-year window.

CONCLUSION

This study reveals that pandemic-era citation inflation in Neuroscience journals was largely temporary and metric-dependent. RoC-based modeling offers a reproducible and adaptable approach for assessing the sustainability of bibliometric trends. These insights can help editors, funders, and academic institutions better understand journal performance, make informed decisions about research dissemination, and refine metrics-based evaluation frameworks in the post-pandemic publishing environment.

摘要

引言

新冠疫情引发了学术出版格局前所未有的变化,尤其是在神经科学和神经药理学等生物医学领域。2020年至2022年期间,几本期刊的引用指标出现了急剧的短期增长。然而,这些激增反映的是可持续影响还是暂时的膨胀仍不确定。本研究旨在通过评估2013年至2023年关键期刊层面指标的变化率(RoC)来分析疫情后的文献计量行为。

方法

对《期刊引证报告》中索引的233种神经科学期刊进行了一项回顾性纵向研究。分析了六个指标:期刊影响因子(JIF)、特征因子得分、即时指数、文章影响力得分、被引半衰期和总被引频次。每年计算每个指标的RoC。构建了具有随机截距和斜率的混合效应模型,以评估纵向轨迹,并确定与三个定义时期相关的变化:疫情前(2013 - 2019年)、疫情期间(2020 - 2022年)和疫情后(2023年)。亚组分析评估了期刊四分位数和类别,以探索影响弹性的差异。

结果

疫情期间(2020 - 2022年),JIF(平均β = +4.85,p = 0.004)、即时指数(β = +6.22,p = 0.002)和总被引频次(β = +5.88,p < 0.00)的RoC显著增加。这些变化在四分位数排名靠前的期刊和神经药理学分类下的期刊中更为突出。相比之下,特征因子得分和文章影响力得分等替代指标在同一时期保持相对稳定。2023年,大多数指标呈现出正常化趋势,JIF和即时指数的RoC显著减速,表明疫情后进行了重新校准。具有持续正向轨迹的期刊主要集中在高影响力集群中,《当代神经药理学》在RoC斜率方面名列前茅。

讨论

研究结果表明,疫情期间引用量的激增主要是暂时的,并且在文献计量指标中有所不同。像JIF和即时指数这样的传统指标对系统性冲击更敏感,而基于影响力的指标(特征因子和文章影响力得分)显示出更高的时间弹性。RoC的应用允许对指标轨迹进行细致入微的解释,并最大限度地减少对短期峰值的误解。局限性包括依赖公开可用数据以及10年窗口内未完全捕捉到的引用行为中的潜在滞后效应。

结论

本研究表明,神经科学期刊在疫情时代的引用膨胀在很大程度上是暂时的且依赖于指标。基于RoC的建模为评估文献计量趋势的可持续性提供了一种可重复且适应性强的方法。这些见解可以帮助编辑、资助者和学术机构更好地理解期刊表现,就研究传播做出明智决策,并在疫情后出版环境中完善基于指标的评估框架。

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