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find Author "GU Yue" 3 results
  • Classification and application of effectiveness-implementation hybrid designs

    Evidence-based evidence translated into health care services requires three conversion processes, preclinical research-clinical research-implementation research, which might take a very long time. In order to speed up the process of research results translated into daily medical practice and health policy, an effectiveness-implementation hybrid design combining the effectiveness research of clinical and implementation research was emerging. This paper introduced the concept, classification and application of effectiveness-implementation hybrid design, to provide references for researchers in this area.

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  • Neurovascular coupling analysis of working memory based on electroencephalography and functional near-infrared spectroscopy

    Working memory is an important foundation for advanced cognitive function. The paper combines the spatiotemporal advantages of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to explore the neurovascular coupling mechanism of working memory. In the data analysis, the convolution matrix of time series of different trials in EEG data and hemodynamic response function (HRF) and the blood oxygen change matrix of fNIRS are extracted as the coupling characteristics. Then, canonical correlation analysis (CCA) is used to calculate the cross correlation between the two modal features. The results show that CCA algorithm can extract the similar change trend of related components between trials, and fNIRS activation of frontal pole region and dorsolateral prefrontal lobe are correlated with the delta, theta, and alpha rhythms of EEG data. This study reveals the mechanism of neurovascular coupling of working memory, and provides a new method for fusion of EEG data and fNIRS data.

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  • A pilot study on the ameliorative effect of "Mom’s Good Mood" on antenatal depression

    Objective To preliminarily assess the ameliorative effect of Mom’s Good Mood (MGM) on the prevalence of antenatal depression based on a pilot study, and to provide evidence for a scale-up study. Methods This study was conducted in Ma’anshan Maternal and Child Health Center as a pilot study of an implementation study conducted in China called the Perinatal Depression Screening and Management (PDSM) program. In 2019, 1 189 participants (gestational week ≤14+6 weeks) were included in the implementation group. Females were recruited in the first trimester and followed up in the second and third trimesters. At each time point, the participants’ depression status was screened by the Edinburgh postpartum depression scale (EPDS), and those who were screened as having depression were provided the MGM intervention. In 2020, 1 708 participants who underwent screening with the EPDS in either the first, second or third trimester at Ma’anshan Maternal and Child Health Center were included in the control group. Mann‒Whitney U test, Chi-square, and multivariate logistic regression analysis were used to compare the EPDS scores and depression prevalence between the control and implementation groups to assess the ameliorative effect of MGM (screening and intervention) on antenatal depression. Results In the first trimester, there were no statistically significant differences in EPDS scores or depression prevalence between the two groups (P>0.05). In the second and third trimesters, both the EPDS scores and depression prevalence of the implementation group were lower than those of the control group (P<0.05). After adjusting for confounders, logistic regression analysis showed that the risks of depression in the implementation group in both the second and third trimesters were lower than those in the control group (ORsecond trimester=0.55, 95%CI 0.37 to 0.81, P=0.003; ORthird trimester=0.51, 95%CI 0.35 to 0.74, P<0.001). Conclusion Implementation of the MGM based on the primary care system can effectively reduce the prevalence of antenatal depression, providing evidence for further scale up.

    Release date:2022-10-25 02:19 Export PDF Favorites Scan
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