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Quantitative scale validation of the Dimensional Anhedonia Rating Scale in the treatment of Chinese patients with major depressive disorder
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作者 Xiaojing Gu Yun-Ai Su +6 位作者 Jingyu Lin Xiaowei Chen Donald M Bushnell Dongjing Fu Carol Jamieson Heather Rozjabek Tianmei Si 《General Psychiatry》 2025年第2期144-152,共9页
Background The patient-reported Dimensional Anhedonia Rating Scale(DARS)has been adapted into Chinese,so there is a need to evaluate its measurement properties in a Chinese population.Aims To evaluate the reliability ... Background The patient-reported Dimensional Anhedonia Rating Scale(DARS)has been adapted into Chinese,so there is a need to evaluate its measurement properties in a Chinese population.Aims To evaluate the reliability and validity of the DARS among Chinese individuals with major depressive disorder(MDD)and its treatment sensitivity in a prospective clinical study.Methods Data were from a multicentre,prospective clinical study(NCT03294525),which recruited both patients with MDD,who were followed for 8 weeks,and healthy controls(HCs),assessed at baseline only.The analysis included confirmatory factor analysis,validity and sensitivity to change.Results Patients’mean(standard deviation(SD))age was 34.8(11.0)years,with 68.7%being female.75.2%of patients with MDD had melancholic features,followed by 63.8%with anxious distress.Patients had experienced MDD for a mean(SD)of 9.2(18)months.DARS scores covered the full range of severity with no major floor or ceiling effects.Confirmatory factor analysis showed adequate fit statistics(comparative fit index 0.976,goodness-of-fit index 0.935 and root mean square error of approximation 0.055).Convergent validity with anhedonia-related measures was confirmed.While the correlation between the DARS and the Hamilton Depression Rating Scale was not strong(r=0.31,baseline),the DARS was found to differentiate between levels of depression.Greater improvements in DARS scores were seen with the Hamilton Rating Scale for Depression responder group(effect size 1.16)compared with the non-responder group(effect size 0.46).Conclusions This study comprehensively evaluated the measurement properties of the DARS using a Chinese population with MDD.Overall,the Chinese version of DARS demonstrates good psychometric properties and has been found to be responsive to change during antidepressant treatment.The DARS is a suitable scale for assessing patient-reported anhedonia in future clinical trials. 展开更多
关键词 RELIABILITY Validity major depressive disorder mdd Quantitative scale validation Chinese population Major Depressive Disorder Dimensional Anhedonia Rating Scale dimensional anhedonia rating scale dars
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以患者为中心的疗效研究:定性和混合方法研究的方法学标准 被引量:2
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作者 Bridget Gaglio Michelle Henton +6 位作者 Amanda Barbeau Emily Evans David Hickam Robin Newhouse Susan Zickmund 蔡思雨(译) 彭晓霞(校) 《英国医学杂志中文版》 2021年第6期335-343,共9页
以患者为中心的疗效研究所(The Patient-Centered Outcomes Research Institute,PCORI)开发的定性和混合方法研究的方法学标准有助于确保研究的设计和实施可以产生人们所需的证据,来回答患者和临床医生关于哪种方法最有效,对谁最有效,... 以患者为中心的疗效研究所(The Patient-Centered Outcomes Research Institute,PCORI)开发的定性和混合方法研究的方法学标准有助于确保研究的设计和实施可以产生人们所需的证据,来回答患者和临床医生关于哪种方法最有效,对谁最有效,在什么情况下最有效的问题。这套标准围绕以患者为中心的疗效研究的相关要素而制定,但也可为其他类型的临床研究提供指导。此标准可用于制定研究方案并对其进行评价、实施研究,以及解释研究结果。标准开发遵循系统的程序,即研究关键方法学问题的范围及其潜在标准,将范围缩小聚焦到最重要的标准上,起草标准初稿,征求同行专家组和广大公众的反馈意见,基于反馈意见确定标准终稿,供PCORI理事会审查并采纳。本文提供了一个例子,说明如何应用这些标准撰写研究计划书。 展开更多
关键词 方法学 计划书 混合方法研究 相关要素 反馈意见 临床医生 设计和实施 疗效研究
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Real-time deep learning-assisted mechano-acoustic system for respiratory diagnosis and multifunctional classification
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作者 Hee Kyu Lee Sang Uk Park +11 位作者 Sunga Kong Heyin Ryu Hyun Bin Kim SangHoon Lee Danbee Kang Sun Hye Shin Ki Jun Yu Juhee Cho Joohoon Kang Il Yong Chun Hye Yun Park Sang Min Won 《npj Flexible Electronics》 2024年第1期192-203,共12页
Epidermally mounted sensors using triaxial accelerometers have been previously used to monitor physiological processes with the implementation of machine learning(ML)algorithm interfaces.The findings from these previo... Epidermally mounted sensors using triaxial accelerometers have been previously used to monitor physiological processes with the implementation of machine learning(ML)algorithm interfaces.The findings from these previous studies have established a strong foundation for the analysis of highresolution,intricate signals,typically through frequency domain conversion.In this study we integrate a wireless mechano-acoustic sensor with a multi-modal deep learning system for the real-time analysis of signals emitted by the laryngeal prominence area of the thyroid cartilage at frequency ranges up to 1 kHz.This interface provides real-time data visualization and communication with the ML server,creating a system that assesses severity of chronic obstructive pulmonary disease and analyzes the user’s speech patterns. 展开更多
关键词 SYSTEM DIAGNOSIS mounted
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