Literature DB >> 25528001

Reliability and validity of a new post-stroke depression scale in Chinese population.

Yingying Yue1, Rui Liu2, Jian Lu2, Xiaojing Wang3, Shining Zhang4, Aiqin Wu5, Qiao Wang6, Yonggui Yuan7.   

Abstract

BACKGROUND: Nowadays there is still a lack of effective method to evaluate post-stroke depression. To distinguish patients with and without depression after stroke reliably, this study proposes a new Post-Stroke Depression Scale (PSDS).
METHODS: PSDS was developed based on various depression scales and clinician experiences. 158 stroke patients who were able to finish PSDS and Hamilton Depression Rating Scale (HDRS) were recruited. Cronbach α, Spearman rank coefficient and Kruskal-Wallis test were respectively used to examine reliability, internal consistency and discriminate validity. Then the Receiver Operating Characteristic (ROC) curve was used to determine the ability of scale and categorized scales to the range of depression. Finally, the factors of the PSDS were classified by average clustering analysis.
RESULTS: The Cronbach α of PSDS was 0.797 (95% CI) indicted a good reliability. The Spearman correlation coefficient between PSDS and HDRS was 0.822 (P<0.001) showed an excellent congruent validity. The discriminate validity displayed significant difference between patients with and without depression (P<0.001). 6/24 was set to be the cut-off value by ROC analysis. Moreover, the different severity was distinguished by the value 6/24, 15/24 and 17/24. LIMITATIONS: The small sample size maybe the main limitation, the larger sample used in different fields according sex, age and side-lesion was needed to verity the results. The cut off value calculated by ROC curve maybe react the severity of the disease to some extent, but it is not absolute.
CONCLUSIONS: PSDS is a valid, reliable and specific tool for evaluating post-stroke depression patients and can be conveniently utilized.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Assessment; Depression; Post-Stroke Depression Scale (PSDS); Stroke

Mesh:

Year:  2014        PMID: 25528001     DOI: 10.1016/j.jad.2014.11.031

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  5 in total

1.  The Role of Neuropeptide Y mRNA Expression Level in Distinguishing Different Types of Depression.

Authors:  Yingying Yue; Haitang Jiang; Yingying Yin; Yuqun Zhang; Jinfeng Liang; Shenghua Li; Jun Wang; Jianxin Lu; Deqin Geng; Aiqin Wu; Yonggui Yuan
Journal:  Front Aging Neurosci       Date:  2016-12-27       Impact factor: 5.750

2.  New opinion on the subtypes of poststroke depression in Chinese stroke survivors.

Authors:  Yingying Yue; Rui Liu; Yin Cao; Yanfeng Wu; Shining Zhang; Huajie Li; Jijun Zhu; Wenhao Jiang; Aiqin Wu; Yonggui Yuan
Journal:  Neuropsychiatr Dis Treat       Date:  2017-03-06       Impact factor: 2.570

3.  Acupuncture for post-stroke depression: a systematic review and meta-analysis.

Authors:  Ran Liu; Kun Zhang; Qiu-Yu Tong; Guang-Wei Cui; Wen Ma; Wei-Dong Shen
Journal:  BMC Complement Med Ther       Date:  2021-04-01

4.  Development and initial validation of a clinical measure to assess symptoms of post-stroke depression in stroke patients at the rehabilitation stage.

Authors:  Junya Chen; Jing Liu; Yawei Zeng; Ruonan Li; Yucui Wang; Weiwei Ding; Junyi Guo; Haiyun Lin; Jufang Li
Journal:  Front Psychol       Date:  2022-07-28

5.  Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression.

Authors:  Yingying Yue; Haitang Jiang; Rui Liu; Yingying Yin; Yuqun Zhang; Jinfeng Liang; Shenghua Li; Jun Wang; Jianxin Lu; Deqin Geng; Aiqin Wu; Yonggui Yuan
Journal:  Oncotarget       Date:  2016-08-23
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.