时间生物学和睡眠研究中人口统计学变量的纳入、报告和分析。

IF 3.2 3区 医学 Q2 NEUROSCIENCES Frontiers in Neuroscience Pub Date : 2024-09-16 eCollection Date: 2024-01-01 DOI:10.3389/fnins.2024.1421026
Selma Tir, Rhiannon White, Manuel Spitschan
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Inclusion, reporting and analysis of demographic variables in chronobiology and sleep research.

Many aspects of sleep and circadian physiology are sensitive to participant-level characteristics. While recent research robustly highlights the importance of considering participant-level demographic information, the extent to which this information is consistently collected, and reported in the literature, remains unclear. This article investigates study sample characteristics within the published sleep and chronobiology research over the past 40 years. 6,777 articles were identified and a random sample of 20% was included. The reporting of sample size, age, sex, gender, ethnicity, level of education, socio-economic status, and profession of the study population was scored, and any reported aggregate summary statistics for these variables were recorded. We observed a significant upward trend in the reporting and analysis of demographic variables in sleep and chronobiology research. However, we found that while > 90% of studies reported age or sex, all other variables were reported in < 25% of cases. Reporting quality was highly variable, indicating an opportunity to standardize reporting guidelines for participant-level characteristics to facilitate Meta analyses.

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来源期刊
Frontiers in Neuroscience
Frontiers in Neuroscience NEUROSCIENCES-
CiteScore
6.20
自引率
4.70%
发文量
2070
审稿时长
14 weeks
期刊介绍: Neural Technology is devoted to the convergence between neurobiology and quantum-, nano- and micro-sciences. In our vision, this interdisciplinary approach should go beyond the technological development of sophisticated methods and should contribute in generating a genuine change in our discipline.
期刊最新文献
Dual-factor model of sleep and diet: a new approach to understanding central fatigue The digital twin in neuroscience: from theory to tailored therapy Corrigendum: Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics. Inclusion, reporting and analysis of demographic variables in chronobiology and sleep research. Study of a precise treatment protocol for patients with consciousness disorders based on the brain network analysis of functional magnetic resonance imaging.
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