Pain Sensitivity Questionnaire: Cross-cultural adaptation and validation of the Greek version.

来自 PUBMED

作者:

Bilika PAivatzidis IKaloudis KGkotzamanis RRuscheweyh RKapreli E

展开

摘要:

The Pain Sensitivity Questionnaire (PSQ) was developed to assess general pain sensitivity. This study aimed to validate the Greek version of PSQ. The questionnaire was translated into Greek (PSQ-GR) and piloted in a small sample of patients with chronic pain (n = 35). A total of 146 chronic pain patients and healthy volunteers completed the PSQ-GR, the Pain Catastrophizing Scale (PCS), Hospital Anxiety and Depression Scale (HADS) and Central Sensitization Inventory (CSI). To evaluate the test-retest reliability, 36 volunteers completed the PSQ-GR twice over 7 ± 2 days. Internal consistency was excellent (Cronbach's alpha 0.90-0.96) for PSQ-total, PSQ-minor, and PSQ-moderate. The Intraclass Correlation Coefficient was estimated at 0.90-0.96 for PSQ-total, PSQ-minor and PSQ-moderate and the SEM was 0.59-0.90 for PSQ-total, PSQ-minor and PSQ-moderate approximately. The smallest detectable change was 0.48 for PSQ-total, 0.47 for PSQ-minor and 0.44 for PSQ-moderate. Positive and significant correlations were observed between PSQ-GR and HADS (r = 0.38, p < 0.01), PCS (r = 0.41, p < 0.01) and CSI (r = 0.30, p < 0.01). Statistically significant differences in PSQ-GR scores were identified between the healthy volunteers and the chronic pain patients. The PSQ-GR is a reliable and valid tool that can assess pain sensitivity in healthy individuals and chronic musculoskeletal pain patients.

收起

展开

DOI:

10.1002/pri.2113

被引量:

0

年份:

2024

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(109)

参考文献(0)

引证文献(0)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读